MATHEMATICS AND NATURAL SCIENCE

Size: px
Start display at page:

Download "MATHEMATICS AND NATURAL SCIENCE"

Transcription

1 MATHEMATICS AND NATURAL SCIENCE Proceedings of the Fifth International Scientific Conference FMNS June 2013 Faculty of Mathematics and Natural Science VOLUME 2 COMPUTER SYSTEMS AND ENGINEERING Dedicated to the 10th anniversary of Department of Computer Systems and Technology South-West University Neofit Rilski Blagoevgrad

2 Fifth International Scientific Conference FMNS2013 South-West University, Faculty of Mathematics and Natural Science June 2013 ORGANIZING COMMITTEE: Honorary Chairman: Prof. Ivan Mirchev, DSc, Rector of the SOUTH-WEST UNIVERSITY "NEOFIT RILSKI" Chairman: Assoc. Prof. Stefan Stefanov, PhD, Dean of the Faculty of Mathematics&Natural Sciences Members: Iliya Gyudzhenov, South-West University Neofit Rilski, Bulgaria Ivan Trenchev, South-West University Neofit Rilski, Bulgaria Ivanka Stankova, South-West University Neofit Rilski, Bulgaria Konstantin Tufekchiev, South-West University Neofit Rilski, Bulgaria Luben Mihov, South-West University Neofit Rilski, Bulgaria Mitko Stoev, South-West University Neofit Rilski, Bulgaria Stanko Shtrakov, South-West University Neofit Rilski, Bulgaria Valentin Hristov, South-West University Neofit Rilski, Bulgaria Grigor Iliev, South-West University Neofit Rilski, Bulgaria Vasilisa Pavlova, Regional Educatioinal Inspectorate-Blagoevgrad, Bulgaria PROGRAM COMMITTEE: Honorary Chairman: Prof. Kiril Chimev, DSc COMPUTER SYSTEMS AND ENGINEERING Members: Albrecht Zur, University of Kiel, Germany Aleksey Bubenchikov, Tomsk State University, Russia Boris Tudjarov, TU- Sofia, Bulgaria Dimitar Dimitrov, South-West University Neofit Rilski, Bulgaria Hubert Roth, University of Siegen, Germany Janos Botzheim, Tokyo Metropolitan University, Japan Kiril Boyanov, Bulgarian Academy of Sciences, Bulgaria Miglena Doncheva, University of Dornbirn, Austria Naoyuki Kubota, Tokyo Metropolitan University, Japan Paul Borza, Transilvania University of Brasov, Romania Shigeru Aomura, Tokyo Metropolitan University, Japan The content of the Proceedings of the International Conference FMNS'2013 will be assigned to two of the EBSCO Publishing Data Bases: Academic Search Complete and Computers & Applied Sciences Complete ISSN

3 Plenary report Information Evolution and Man Kiril Boyanov IICT-BAS, Sofia, Bulgaria 1. INTRODUCTION The increasing volume of information flow and the social networks lead to significant alteration in our perceptions followed by a leap into more disordered and unstructured conclusions which a human being takes. Our minds get accustomed to working with partial information and separate facts without them being linked to each other. As a result we find more difficulties when coping with larger works and large-scale compositions which require time and attention. When reading we gradually lose our ability to concentrate and remember images and ideas or to find meaning and patterns in relatively random elements. The social networks weaken and in time lead to a total loss of some useful habits which we have previously established. The use of social networks as a basis for spreading information is growing exponentially. The largest so far social network Facebook has more than 650 million active users registered between 2004 and 2010 [1]. According to the statistics each user is connected to another 130, and creates 90 posts including feeds, notes, photos and links to other sources each month. Users spend more than 700 billion minutes in Facebook [2]. Throughout the human history of social development the access to more information has practically allowed us to increase our knowledge. The introduction of writing is part of this process, and yet it has also acted as a limit to independent reasoning. Through writing we can store information and enforce our memory. Ever since the time of Platon has it been recognised that memory should be used as a mean to increase knowledge and to enhance structural thinking. The use of writing, as a form of external memory is widespread in today s society. 2. WAYS TO TRANSFER INFORMATION (SPEECH, SOUND, IMAGE) People have initially communicated with each other through discussions, by bringing up memories and forwarding basic information, stories and events from one generation to another. With the birth of writing we start storing information and find the ability to structure it. 3

4 It should be noted that a flow of information which is transmitted via speech is relatively limited. The volume of information which can be transferred by speaking can easily be proven as limited [3] Speech transfer If we consider one of the ways of information transfer the speech some rough calculation can be made. Each character is coded with 6 bits (binary). If we assume that in average, a word consists of 5 characters, one needs 60 bits for two words. Man can talk no faster than 3-4 words per second, which means that we can assume the upper boundary of 200 bit/sec as the one used by humans for information exchange (having 8 bits for coding and 4 words 160 bits/sec, with compression up to 4 bits and 4 words 80 bits/sec). The possibilities of the human brain for immediate use of character information, is huge. Let assume that a talented actor can memorize about 200 pages text, which he can repeat, after learning it by heart. According the standards, 1 page has 66 characters in a line and 30 lines per page all together 1980 characters. When coding 1 character with 8 bits we got 1980 x 8 =~16 Kb per page. With maximum speed of reading of 200 bits/sec, the time for reading of those 200 pages is: (200*16*10 3 )/200 = 16*10 3 = ~16*10 3 sec = ~ 4.44 hours The volume of transferred information is about 400 KB. In fact (actually) a man reads a page for some 90 sec, i.e. with coding of 8 bits per character = ~176 bits/sec, when we have 6 bits per character = ~ 132 bits/sec. So, an upper boundary of 200 bits/sec. can be accepted Sound transfer Let us consider a piece of music. We suggest (for simplicity) the Minute Waltz of Chopin, which is played by good pianists for 1 minute. The piano has 85 keys and for the coding of each one, we assign 1 bit (on, off). For the strength of the sound, from the weakest (pianissimo) to the strongest (fortissimo), we assign 10 bits. This scale has 1024 grades, enough for a good master. For Chopin s waltz if we use 50 keys (out of 85), 50 bits will be needed in addition to the 10 bits for the volume, which comes altogether to 60 bits. In the musical score, one can count 730 notes (in general, in case we regard the chords as one position). In such case, the speed of transfer will be: ( 730*60 ) / 60 = ~ 730 bits/sec Or a bit more, in case we include notes with longer duration.

5 Plenary report We can make the conclusion that there is 3 to 4 times bigger speed for transferring information, in case we use sound (tune). If we compare a good musician to an actor, the former has to memorize several time bigger information than the latter (for some 3-6 hours), maybe even more, when regarding the musical score of big musical compositions like symphonies, requiems, etc. It is not our task or intention to compare the brain abilities of the actor and the musician. The conclusion is linked to the fact, that using more musical tunes leads to transfer of more information. The volume of the transferred information for 4.4 hours is = 4.4 * 3600 * 730 = b, which is approximately 1.43 MB 4 times bigger volume. We can think that a thunderstorm or sea waves will be described with higher information speed (bits/sec) and correctness if using sound than speech. If we look at some Eastern languages (Japanese, Chinese), we shall notice that some words express concepts and we can conclude that for the time, that European languages transfer some 200 bits/sec, the ancient languages transfer bigger quantity bits (i.e. more information if we measure the quantity). It is curious to know whether the ancient languages, preceding in terms of history the European, are more perfect in terms of information transfer. Or the elaboration of those languages was aimed at transferring more information for a shorter period of time. For example the speed of communication can be improved more by overloading the words with several meanings. Chinese language is a good example on this: ma = mother, horse and question. Also notation of words can be improved by using reduced instruction set, also like in Chinese: <mother> = <woman> + <horse> <house> = <roof> + <pig> A natural obstruction is that using more tunes leads to more possibilities for errors (i.e. wrong understanding of the expressions) Image transfer Transferring information by image is faster and more effective. Watching modern monitors, our eye accepts for 1 second several hundred thousand bits (in a quality image, there are several mega pixels and not all shades are being percept). This imposed the cinema, TV and other image devices as the faster source of big volume of information. They are also the most informative, in terms of acceptance and processing by the human brain. Until the present moment, the education and acceptance of new facts and knowledge was linked to oral explanation and visual materials. Knowledge was gained also from books. In both cases, the sent and available information lets human brain to process it. Depending on the 5

6 intellectual abilities of the person, the processing and rationalization of the information was quicker or slower, but there was the option of explanations, the visual materials or the written information was available to the learner. Modern tools allow even better quality of visualization by image projection but this approach also allows control of time, so that the percept information can be realized. One can state that the process of information transfer was faster than the process of its processing and man had enough time to grasp and realize the presented information. With the mass introduction of TV, computers with significant abilities for visualization, the flow of information has increased significantly and the need for faster processing and realization of that information is evident. The resurrection of interactive methods for education allows the process of transfer of information to go in parallel with the one of its realization. It is clear that to explain to child what is cat is faster with picture than by oral explanation. The continuous information flow sometimes requires swift reaction by a person, depending on the situation as in emergencies or when fast and effective decisions are required in areas, still controlled by man transport, emergency operations, industrial processes, etc. This implies that modern man has to increase his abilities not only for faster understanding and grasping of information but also for its faster processing. Both requirements assume getting more abilities and skills through new approaches. The development or perfection of human senses can be achieved by proper training and education: quick image recognition, effective filtering of background information, increased ability for sight and hearing. It is clear that individual abilities of each person should be taken into account. The fact, that abilities are ever improved by system training and using various approaches shows that using that regular work can lead to improved individual qualities in accordance to the demanded particular requirements. One can see two scenarios here: creation of abilities by purposeful education of people i.e. creation of intelligent commandos. The other scenario is using gene engineering creating cultivated modern societies. Both approaches do not provide good forcasts. Even now, Internet divides society to those, seeking fun and strong emotions and the ones seeking knowledge. The first group will soon form not very well educated class or group, which we can call user. The second group we can place at the so called educated elite (or intelligent society). This will lead invevitabely to division of society and a future destructible conflict can be expected in either near future or later on, taking into consideration national characteristics. In short one might expect a digital division of society and the question When destructible social conflicts will begin? remains. They will get bigger and stronger also due to the increasing gap between rich and poor. The second scenario of improving the qualities and skills of people, by changing the gene material does not lead to good forecast either. Human 6

7 Plenary report senses can not improve endlessly and there will be a moment, when a dedeformation of organs will occur, having unforeseen consequences. Whatever improvement is carried out on a particular organism, there is a limit it is clear that 100 meters can not be run for 1 second. The faster processing of information supposes the progress of abstract thinking and the potential for physiological and social generalization of the processes. Undoubtedly for people with various tendencies in certain societies, using certain approaches can lead to solving complex abstract or practical tasks. For others, there can be significant success in summarizing real humanitarian situations or the creation of pieces of art. The first group can work well in the field of technology in the name of mankind s prosperity, while the second will be leading for their spiritual enlightening. One can present the hypothesis that the human organism was and will be developing in the direction of increasing its abilities for maximal perception and fastest processing of information. Let us consider the possible boundaries for speed of transferred information. According to some examples from university classes [4], during the use of light in the micron scope (1.3 microns), where the attenuation is almost a constant, for example for λ * 0.17*10-6, we have (1) df c c λ λ. f = c; = ; f = 2 2 dλ λ λ i. e. f ,17.10 = 6 2 (1,3.10 ) 6 = or 30 THz Using Shannon s formula for the speed of information transfer [5] we get: (2) S = f 1n ( S N. 200 ) ln ( ) 0,6 Pb / s, Having a ratio signal/noise = = Even if we consider electromagnetic radiation with shorter waves, the speed of transmission will be limited to tens Pb/s. Is there a limit of the speed theoretically? As S/N is limited, the increase of f is also limited; c is constant, so theoretically it is hardly possible to achieve speed of several Exab/s. Processing of information. Let us consider the possibilities of computer processing. Modern speeds of processing are in the range of PFlops/s with the tendency of achieving ExaFlops/s. Reaching the next order will be difficult due to technological and power problems. Energy 7

8 losses (power consumption + cooling) can be unsuitable from environmental point of view. The problem can be solved by the introduction of new principles of computing for example quantum computing, molecular computers using other principles of computing, though some restrictions can arise. This raises the question of perceiving of the results of the processed information and its use in terms of expedience. In certain cases, human brain can be used to take decisions in real time, even when using computer systems, which he must get going. This means that his reaction won t be in time i.e. there won t be the necessary result, hence it is not expedient. 3. MAN AND THE DIGITAL WORLD As far as human s intellect is related to the brain s capacity, the relationship between its development and the introduction of new technology stands as a question of high importance. Some papers already describe technical approaches that allow faster introduction of information and also ways to use it more rational when managing real systems [6][7][8][9]. This is obviously a process that is limited in the long run, a question that can now be left for a solution. It is associated with certain paradoxes is there a limit to the knowledge one can gain and can one reach this limit. If there is no limit to a person s potential knowledge then this knowledge will constantly grow up to a level, providing human s consciousness a new way of being. How will this development affect the group of people who are directly involved with physical labour and cannot reach the minimum intelligence level? Will we reach to a rift between the two groups or will we search for a mutually beneficial solution a matter of research under certain assumptions, which is both technological as well as philosophical. The more likely scenario is that conflicts will arise, since earth s resources will be depleted, and people with higher intellectual standing will be able to deal with certain diseases, the cures of which will be out of grasp for the other group. But without this other group the food issue should be viewed in a whole different perspective. What will this society be one of highly developed intellectuals who will use modern technology to supply their basic necessities, or will we inevitably pass through a global conflict leading to an uncertain outcome about the preservation of our civilization? 4. PROCESSING INFORMATION. COMPUTER-MAN If we assume that there is a given connection between a human s and a computer s methods of processing information, we can roughly derive the 8

9 Plenary report following parallels. Durring the administration of the different activities in the computer systems, a certain part of the RAM is kept for the preservation of the base supervising program (SP). Looking into the development of the computer systems, the supervising program has taken from 10% to 20 % of the RAM. What is more, in order to use the full capacity of the computer, there is a continuous exchange between the RAM and the external memory. Let us assume that roughly 20% of the memory preserved for administration provides for the use of the rest of the RAM in a wide variety of tasks. It should be noted that an increasing complexity of tasks corresponds to an increasing need for a larger quantity of SP and RAM. A parallel with the human brain can be made. The number of neurons is regarded to be around [10] and the number of connections is around (synopsis). According to research [11], [12], out of approximately 86 billion neurons, 69 billion are located in the brain and 16.3 billion find place in the cortex. It is possible that these 16.3 billion perform functions similar to the SP. We will focus with more detail into the supervising program which usually takes place in a protected part of the RAM. The SP aims to ensure functionality of the computer system by using RAM and external memory. The RAM hosts the data that is to be processed. Whether it will be hosted it pages intended to solve certain task in a multi-program mode, or whether batch-processing will be performed is an issue related to the performance of the computer system, and naturally its organization and architecture. In any case, however, SP aims also to ensure completion of the programs and their interactions with the environment (peripherals). We take it clear that the SP cannot pro-create new features within itself, but rather the system programmer or designer will add any amendments if needed. I.e. once confined, the SP cannot be modified during the execution of a specific task. Corrections can only be made in a certain time intervals depending on the requirements and functionality set by the designer. Figuratively speaking, the SP cannot cultivate and acquire new skills. In the human brain, things look way more different. A fixed portion of the brain cells have a task of managing operations of the other cells, whilst constantly introducing them with new information subject to storage and processing. The work process in the brain differs from the relationship SP-RAM (in the computer system) as a certain minimum of initial functions should be introduced which would serve to accumulate information in the brain cells. This process begins its development with the birth of a human being when he/she starts to percept and sense. Part of the information is stored, but at the same time is processed by those brain cells responsible for carrying out the connections. It is thus that we start accumulating a certain volume of 9

10 information in our brain which can be perceived through sight, hearing, touch, smell, and any other form of sensing known to the human body. This is a volume of information that constantly increases but managing the links between this information is carried out by the corresponding CPB (Control Program of the brain), which occupies part of the brain cells. An interesting fact [10] is that each neuron can carry out 7000 connections (synopsis). Within time, the data accumulated from the external environment grows more and more, resulting in a need for an improved supervising system so that better processing of this information can be achieved. This respectively leads to improving a human s organism actions in his/her environment. In such respect we can establish similarities with a computer system carrying out tasks for real-time processes. In the same way that these actions can be associated with food gathering, they can also be associated with obtaining new knowledge about the surrounding environment. Such knowledge may improve a human s survival skills and/or may contribute for acquiring useful information in respect to his/her activities. In other words, we derive at a process where the volume of information is increased and at the same time the CPB is improved. Unlike a computer system, however, this improvement in the CPB is obtained thanks to training and self-training due to the contact between different personalities, and also thanks to the accumulated volume of information which allows management capabilities to grow. I.e. an interesting feature is that the more information the human brain acquires, the more complicated it becomes to manage this information in respect to survival related activities or development of the human s skills and intelligence. Moreover, giving progress to the CPB by the creation of new neuron cells will further improve the functionality of the whole brain system. That is to periphrases the hypothesis as follows: the larger the volume of accumulated information and the improved quality and speed of its processing should lead to an extended life expectancy. There is another interesting feature in the case of computer systems. In this case, the SP and volume of memory for a certain generation is fixed and cannot be substantially altered, and only a next generation can be designed with better functionality, increased memory, increased volume of the SP, etc. However, in the case of a human being this is all performed through an internally-dependent process. I.e., improving CPB is related to the increased volume of information which a person must perceive. As observed this volume increases over time, which leased to an even increased number of connections between the separate brain cells. And having in mind that there are 100 billion cells with 86 billion neurons and around 16 billion connections all of which responsible for the brain s functionality, there will yet be portions of the memory, which could be utilized, i.e. we should be able to continue adopting new information. When 10

11 Plenary report considering a rough estimate of around 10 GB RAM in the human brain and several GB of CPB, the human s potential is far from exhausted. Since it is estimated that the total volume of the world s information at present is around several exabytes, then it is logical that the information used by one individual is considerably smaller, i.e. K <<1. Veff app Kapp =, V where K app - coefficient of applicability, V eff - effective volume of used information, V - Volume of information. 5. INFORMATION AND EDUCATION The access to a larger volume of information that allows individuals to expand their knowledge requires changes in the educational system. Within the educational field there have already been some studies developing new methods and approaches to education. Without considering the entirety of the field there are some interesting examples. Implementation of new techniques is evident in the training of tutors in the field of computer science due to the high applicability. Paper [13] discusses not only the demand of greater number of teachers but also the need to train them according to the technological developments. The methods of education are the essence of the educational system. A greater percentage of academic graduates and practical trainees learn how to do the work they have studied for on the job rather than at university. On many instances this proves unsatisfactory for the employer which would require the educational providers to implement more focused and practical training. On one hand a future employee needs to be practically prepared in order to satisfy the requirements of the employer. On the other hand the limited study of basic theoretical theory makes it more difficult for professionals to acquire the new developments which would eventually be introduced in their field. A solution to this problem would be the constant improvement of one's knowledge and qualifications, or continuous education throughout one s lifetime. The question then becomes what changes need to be introduced by the educational providers in order to implement such improvements. It is time to start making professional administrators aware of the development, needs and requirements of the different subjects thought in universities - a goal which depends on many things in order to be realised. For instance the people writing educational policies are not necessarily prepared professionally for the job or might not have the financial motivation. On the one hand the usually long term of employment of the heads of the university departments gives a guarantee to the public that traditions and best 11

12 practices will be observed. On the other hand this academic conservatism is harmful to the quickly developing digital field of education and does not allow for an account to be made of the realities of the spiritual and public life. Special attention should be given to economic and computer science universities which provide education in some of the vastly changing fields. The introduction of computer technology is dynamically taking place in almost all aspects of modern education starting with natural sciences, through humanities and social sciences and even including arts [14]. Although this technology brings many advantages throughout its wide range of applications, there are also some certain drawbacks. An important element which restricts some of these disadvantages but is yet absent in our educational system is the code of ethics. The implication of such field is crucial in order to address a few existing ethical problems: Protection of copyrights from plagiarism; Sharing materials related to narcotics, alcohol, porn etc, via the computer networks; Control over the sites of educational institutions which should assess if any ethical code is actually conducted; Unbiased assessments of students, teachers, etc. 6. MAN AND DIGITAL SOCIETY The Internet has changed the political and social realities, creating new opportunities for communication between people, expanding our horizons. The social networks and electronic media have set the roots of forming a digital society where the voice of social formations is increasingly being heard and recognised. The birth of this digital society implies a development of newly established communication, networking and literacy. This new literacy, in turn, includes active communication and an involvement of all participant members. In reality this should involve a combination of both the technical and social skills of the participants in this society. Just as our current traditional literacy and skills open the doors to the working and social processes, so should the digital literacy and digital skills provide certain abilities and confidence to become an active member of the digital society. The in-depth studies and implementations of computer and communication technology can expand our knowledge and skills from a childhood age improving the quality of the digital society. The use of mobile communication and mobile technology has significantly improved our access to information at any time. Within the already established cyber space the access to information is related to two important (user) aspects. 12

13 Plenary report The first aspect is the behaviour of the users. It can be recognised, for example, that when we use roads, public transport, driving, etc. we keep compliance with certain requirements and standards of behaviour. This implies that we achieve a certain level of literacy. In the digital society, one should in the same way establish certain behaviour and habits. Literature [15] identifies several important areas of behaviour which users of the digital society have to keep in compliance with: etiquette, communication, education, access, trade, responsibility, rights, safety and security. Other authors [16] suggest four key areas: digital compliance, digital ethics, digital sensibility and digital participation. The second aspect is related to cyber threats and their relationship to the user s behaviour in the digital society. The exponential growth of the use of Internet in economic, public and social areas has led to a tremendous increase in cyber attacks and threats. The existing firewalls are not always well-proofed requiring more responsibility and considerable efforts on the side of security experts [17]. 7. PRIVACY OF INFORMATION Protecting information is becoming a more and more serious problem. With the internet era and the expanding volumes of data uploaded online it is a challenge to find new preventive methods. In retrospect, one would find comparable dangers to privacy of information even before the invention of the computer. For example, even though the type of security used on social security cards and key-cards is not even comparable to the sophisticated protection used for online social networks the risks and dangers are alike. Computer systems, local network and internet in general have differences in vulnerability to breaches, but the types of the problems posed are similar. The greatest danger to social network users is the breach (loss) of private information. According to [2] security of information researchers have estimated that up to July 2010, the private information of more than 100 million Facebook users is publicly accessible through the search engines. Several other threats are posed such as identity theft, debit and credit cards fraud and the like. The so called "hackers" attach social networks for one or more of the following reasons: The large number of users Abundance of private information that might be used for different purposes Easy access the such networks The high level of trust amongst users The variety of links to different applications allows more than one attack to be made 13

14 Opportunity for spreading viruses The increasing number of ways to breach the privacy of information requires serious protection. The traditional protective methods such as cryptography, security protocols and insurance are no longer sufficient. The main goal of researchers is to perform the necessary analysis of protocols and methods of protection of privacy of information and to suggest entirely new approaches and a paradigm adequate to the new security requirements [18]. 8. CONCLUSIONS The rapidly growing flow of information via the Internet and other sources sets enormous challenges and stress in our lives. It is only natural that this will influence both positively and negatively human and society. Appropriate measures and programs should be introduced as soon as possible. These should be embraced by all age groups, starting as early as preschool, otherwise the consequences might evolve to be hard to predict. 9. REFERENCES 14 [1] Carlson, N. Facebook Has More Than 600 Million Users, Goldman Tells Clients, Business Insider, Online January 15, 2011, Available at: million-users-goldman-tells-clients [2] Saeed A, Th. M. Chen, O. Alzubi, Malicious and Spam Posts in Online Social Networks, Computer, September 2011, p. 23. [3] K. Boyanov, On the Measurement of Quantity of Information on Speech, Sound and Image, and their Link with the Information Processing, Proceedings of Joint Informational Conference on Human-Centered Computer Environments [HCCE 2012], March, 2012, Aizu-Wakamatsu, Japan. [4] A. Tanenbaum, Computer Network, 4th Edition, 2003, Prentice Hall, Ch.2, 2.2. [5] C. E. Shannon (January 1949). Communication in the presence of noise (PDF). Proc. Institute of Radio Engineers vol. 37 (1): [6] A. Schmidt and E. Churchill, Interaction beyond the Keyboard, Computer, April 2012 p. 21. [7] H. Gellersen and F. Block, Novel Interactions on the Keyboard, Computer, April 2012 p. 36. [8] A. Riener. Gestural Interaction in Vehicular Applications, Computer, Appril 2012, p. 42.

15 Plenary report [9] M. Begudouin and all Multisurface interaction in the WILO Room, Computer, April [10] Draclman D., Do we have brain to spare?, Neurology 64(12)р [11] Williams R., Herrup K., The control of neuron number, Annual Review of Neuro science 12, p [12] Azevedo F., Carvalho L., Grinberg L., et al Equal numbers of neuronal and noneuronal cells make the human brain an isometrically scalet-up primate brain. The Journal of Comparative Neurology 513(5), April [13] M. Guzdial, Learning How to Prepare Computer Science High School Teachers, Computer, October 2011, p. 95. [14] N. Holmes., Digital Machinery and Analog Brains, Computer, October 2011, p [15] Ribble M., Bailey G., Ross T., Digital Citizenship Addressing Appropriate Technology Behavior, Learning& Leading with Technology, September 2004, vol. 32, No 1, pp [16] Yang H., Oh K., A Study of the Digital Citizenship. The International Journal of Policy Studies, Korean Association for Public Studies, [17] Боянов Л., Зл. Минчев, К. Боянов, Някои киберзаплахи в дигиталното общество, Автоматика и Информатика, кн. 3, [18] R. Rodrigo, P. Najera, J. Lopezi, Securing the Internet Things, Computer, September 2011, p

16 16

17 Computer Systems and Engineering Multi-modal Perception for Human-friendly Robot Partners with Smart Phones based on Computational Intelligence Naoyuki Kubota *1, Yuichiro Toda *1, Janos Botzheim *1,2, and Boris Tudjarov *3 1 Tokyo Metropolitan University, Tokyo, Japan 2 Szechenyi Istvan University, Gyor, Hungary 3 Technical University of Sofia, Sofia, Bulgaria Abstract: This paper proposes an intelligent information processing method for multi-modal perception of a human-friendly robot partner based on various types of sensors built in a smart phone. First, we explain the hardware specification of a robot partner using a smart phone. Next, we propose an integration method of measurement data obtained by several sensors in the smart phone to estimate human interaction mode by computational intelligence techniques. Finally, we show several experimental results of the proposed method using the robot partner, and discuss the future direction. Keywords: Intelligent Robots, Sensor Fusion, Computational Intelligence, Natural Communication. 1. INTRODUCTION Recently, various types of smart phone and tablet PC have been developed, and their price is decreasing year by year [1]. Furthermore, the embedded system technology enables to miniaturize such a device and to integrate it with many sensors and other equipment. As a result, we can get a mechatronics device including many sensors, wireless communication systems, GPU and CPU composed of multiple cores with low price. Furthermore, elderly people unfamiliar with information home appliances also have easily started using tablet PC [2], because touch panels or touch interface have been popularized at ticket machines and information services in public areas. Therefore, we started the development project on on-table small size of human-friendly robot partners called iphonoid and ipadrone based on smart phone or tablet PC to realize information support to elderly people. [3,4]. 17

18 We can discuss three different styles of robot partners using a smart phone or tablet PC from the interactive point of view: physical robot partner, pocket robot partner, and virtual robot partner [5]. Each style of robot partners is different, but the interaction modes depend on each other, and we interact with the robot partner with the same knowledge on personal information, life logs, and interaction rules. In this paper, we propose a method of estimating human interaction modes based on computational intelligence techniques by using measurement data of sensors a smart phone or a tablet PC equipped with. This paper is organized as follows. Section 2 explains the hardware specification of robot partners developed in this study. Section 3 proposes the methods of estimating human interaction mode and estimating human behaviors. Section 4 shows several experimental results of human-friendly robot partners. Finally, we summarize this paper, and discuss the future direction to realize human-friendly robot partners. 2. HUMAN FRIENDLY ROBOT PARTNERS We have developed on-table small size of robot partners called iphonoid and ipadrone (Figs.1 (a) and (b)). Since a smart phone is equipped with various sensors such as gyro, accelerometer, illumination sensor, touch interface, compass, two cameras, and microphone in addition to CPU and GPU, the robot base should have composed of actuators, motor drivers, and communication units at least. The mobile base is equipped in the bottom (Fig.1), but basically we don t use the mobile base on the table for safety s sake. In order to control the actuators of a robot partner from the smart phone or tablet PC, we can use wireless LAN and wireless PAN (Bluetooth) in addition to a wired serial communication. Basically, human detection, object detection, and voice recognition are done by the smart phone or tablet PC. Furthermore, touch interface is used as a direct communication method. When a person touches the right side on the display, the facial expression changes and voice recognition starts (Fig.2 (a)). Based on the perceptual information, the robot partner makes utterance with gestures (Fig.2 (b)). (a) iphonoid (b) ipadrone Fig.1: Robot partners using a smart phone and a tablet PC. 18

19 Computer Systems and Engineering (a) Voice recognition (b) A gesture Fig.2: Robot behaviors for social communication with people. 3. MULTI-MODAL PERCEPTION BASED ON SENSOR FUSION 3.1. Human Interaction Modes In this paper, since we use the facial expression on the display for human interaction (see Figs. 1 and 2), the robot partner should estimate the human interaction mode: (a) the physical robot partner mode (attached to the robot base), (b) pocket robot partner mode (being removed from the robot base), or (c) other mode (on the table, in the bag, and so on). We use the values of acceleration, attitude, and luminance, and apply a fuzzy spiking neural network (FSNN) [6,7] using a simple spike response model with Gaussian membership functions to estimate the human interaction mode. A high pass filter is used to calculate the acceleration from data measured by the accelerometer. The attitude is calculated by measurement data of accelerometer, gyroscope, and digital compass. The luminance is calculated from the images measured by cameras. The internal state h i (t) of the i-th spiking neuron at the discrete time t is calculated as follows: (1) h i (t) = tanh(h i syn (t) + h i ext (t) + h i ref (t)), where h i syn (t) includes the pulse outputs from other neurons, h i ref (t) is used for representing the refractoriness of the neuron, h i ext (t) is the input to the ith neuron from the external environment. The hyperbolic tangent function is used to avoid the bursting of neuronal fires. The external input, h i ext (t)is calculated based on Gaussian membership functions: 19

20 (2) h =,.,, (3) 20 Furthermore, h i syn (t) indicates the output pulses from other neurons: h =,.h 1, where w j,i is a weight coefficient from the jth to the ith neuron; h j PSP (t) is the presynaptic action potential (PSP) approximately transmitted from the jth neuron at the discrete time t; N is the number of neurons. When the internal action potential of the ith neuron is larger than the predefined threshold, a pulse is outputted as follows: (4) = h 0 h where q pul is a threshold for firing. Furthermore, R is subtracted from the refractoriness value as follows: (5) h =. h 1 1 =1.h 1 h where γ ref is a discount rate and R>0. The spiking neurons are interconnected, and the presynaptic spike output is transmitted to the connected neuron according to the PSP with the weight connection. The PSP is calculated as follows: (6) h = 1 =1.h 1 h where γ PSP is the discount rate (0< γ PSP <1.0). Therefore, the postsynaptic action potential is excitatory if the weight parameter w j,i is positive. We apply (µ+λ)-evolution Strategy (ES) for the improvement of the parameters of the Gaussian membership functions. In (µ+λ)-es, µ and λ indicate the number of parents and the number of offspring produced in a single generation, respectively [8]. We use (µ+1)-es to enhance the local hill-

21 Computer Systems and Engineering climbing search as a continuous model of generations, which eliminates and generates one individual in a generation. (µ+1)-es is considered as a steady-state genetic algorithm (SSGA) [9]. A candidate solution is composed of numerical parameters corresponding to the central value, the width, and the contribution of fuzzy membership functions: (7) g k = [ g k,1 g k,2 g k,3... g k,i ] = [ a k,1,1 b k,1,1 n k,1,1... n k,n,m ] where n is the number of human interaction modes; m is the number of inputs; l = n m is the chromosome length of the kth candidate solution. The fitness value of the kth candidate solution is calculated by the following equation: (8), where f k,i is the number of correct estimation rates of the ith human interaction mode. In (µ+1)-es, only an existing solution is replaced with the candidate solution generated by crossover and mutation. We use elitist crossover and adaptive mutation. Elitist crossover randomly selects one individual, and generates an individual by combining genetic information between the selected individual and the best individual in order to obtain feasible solutions from the previous estimation result rapidly. Here we can use the local evaluation values of the human interaction estimation Multi-modal Interaction The robot partner starts the multi-modal interaction after a smart phone is attached to the robot base. We use touch interface on the smart phone or tablet PC as the nearest interaction with a robot partner. The facial parts are displayed as icons for the touch interface in the display (Fig.2 (a)). Since the aim of this study is to realize information support to elderly people through the multi-modal interaction, the robot partner provides elderly people with their required information through the touch interface. The ear icon is used for direct voice recognition because it is difficult to perform high performance of voice recognition in the daily communication with the robot partner. If the person touches the mouth icon, then the ear icon appears, and the voice recognition starts. The voice recognition is done by Nuance Mobile Developer Program (NMDP). NMDP is a self-service program for the developers of ios and Android application. In this way, the total performance of multi-modal communication can be improved by combining several communication modalities of touch interface, voice recogni- 21

22 tion, and image processing. The conversation system is composed of (A) daily conversation mode, (B) information support mode, and (C) scenario conversation mode [4,5]. We use two cameras (front and rear cameras) the smart phone equipped with. Basically, we obtain time-series of images in RGB color space. In order to detect a human considered as a moving object, we use (1) gray scale conversion from the color image by YUV model, (2) differential extraction, (3) simple color extraction, and (4) ES [8] based on template matching for extracting a human shape from the background image. The sequence of human hand positions can be used to extract a spatiotemporal pattern of human behaviors. Here two layers of spiking neural network (SNN) using a simple spike response model for human motion extraction are applied to reduce the computational cost. In the first layer, spiking neurons are used to extract the moving direction and other motions listed in Table 1. By using the change of position of a human face or hand, the neuron corresponding to its direction is fired. In the second layer, the excitatory presynaptic potential (EPSP) based on firing patterns is used to estimate human behaviors listed in Table 2. The human behaviors of (0) No people, (1) Approaching, and (2) Leaving are simply estimated by the change of human position and the size of template. The human behavior of (4) Sitting is estimated by the relative position from the robot. The human behavior of (5) Interacting is estimated by motion extraction, and the human behavior of (6) Touching is directly recognized by the touch interface of the robot face. Tab. 1: Features used for motion extraction. ID Motion ID Motion ID Motion 0 no motion 6 d5 direction 12 area size 1 d0 direction 7 d6 direction 13 upper position 2 d1 direction 8 d7 direction 14 middle position 3 d2 direction 9 stoping 15 lower position 4 d3 direction 10 extending 5 d4 direction 11 reducing Tab. 2: Human behaviours. ID Behavior ID Behavior 0 no people 4 sitting 1 approaching 5 interacting 2 leaving 6 touching 3 standing 22

23 Computer Systems and Engineering 4. EXPERIMENTAL RESULTS This section shows experimental results of the proposed method using a robot partner. The number of individuals of (µ+1)-es for fuzzy inference is 100, and the number of evaluation (iteration) times is Figure 3 illustrates experimental results of the estimation of human interaction modes by the proposed method. We conducted off-line learning after obtaining teaching data beforehand. In the experimental result (Fig.3 (a)), the person put iphone on the table with making the display prone ((1) in Fig.3 (a)). As a result, since the luminance was very low, the rear camera was activated ((2) in Fig.3 (a)). After several second, the person overturned the iphone ((3) in Fig.3 (a)). Next, the person took the iphone ((4) in Fig.3 (a)), and attached the iphone to the robot s base ((5) in Fig.3 (a)). In the initialization of the fuzzy inference rules, we used the average and standard deviation of the input data of the teaching signals. Figure 3 (b) shows an estimation result using the initial values of the fuzzy inference rules before learning. After updating the fuzzy inference rules by (µ+1)-es, the performance of the estimation of human interaction mode was improved (Fig.3 (c)). Inputs to FSNN Acceleration Roll (Attitude) Luminance 1.0 (1) (2) (3) (4) (5) Time Steps Human Interaction Mode Carring iphonoid Back Side Front Side 1 (a) Inputs to FSNN Teaching Signal Time Steps (b) An estimation result before learning Estimation Result Human Interaction Mode Carring iphonoid Teaching Signal Estimation Result Back Side Front Side Time Steps (c) An estimation result after learning Fig. 3: Estimation results of human interaction mode. Next, we present experimental results of human interaction. The image size of a camera is reduced to 120 x 160. The number of individuals (candidate templates) of (µ+1)-es for the image processing is 100, and the num- 23

24 ber of evaluation (iteration) times for the image processing is 150. Figure 4 depicts the snapshots of attention range, human detection, human motion, and object detection. The result of image processing is shown in the left side, and the attention range is drawn by a red box in the right side. A person showed a bottle (a), and showed a hand gesture (c). Since the attention range is focused on the moving object, and the robot partner traced the movement of the bottle. After the person had put the bottle on the table, the robot partner paid attention to the human face. Next, the robot partner found the human hand gesture, and extracted its human hand motion pattern. In this way, the robot partner tried to pay attention to human motion and gestures to realize the interaction with a person. (a) (b) (c) Fig. 4: Snapshots of robot gestures. 5. SUMMARY In this paper, we proposed a method of estimating human interaction mode using two cameras, accelerometer, and gyro. First, we explained the robot partners developed in this paper. Next, we proposed an estimation method of human interaction mode using a fuzzy spiking neural network based on a simple spike response model with Gaussian membership functions. Furthermore, we proposed a method of tuning fuzzy inference rules based on evolution strategy. In the experimental results, we showed, that the proposed method is able to estimate human interaction modes based on the iphone s sensors. As a future work, we intend to improve the learning performance according to human life logs, and propose an estimation method of more types of human interaction modes. 6. REFERENCES [1] [2] [3] D. Tang, B. Yusuf, J. Botzheim, N. Kubota, and I. A. Sulistijono, Robot Partner Development Using Emotional Model Based on Sen- 24

25 Computer Systems and Engineering sor Network, Proc. (CD-ROM) of IEEE Conference on Control, Systems and Industrial Informatics (ICCSII 2012), pp , [4] N. Kubota, Y. Toda, Multi-modal Communication for Human-friendly Robot Partners in Informationally Structured Space, IEEE Transaction on Systems, Man, and Cybernetics-Part C, vol. 42, no. 6, pp , [5] N. Kubota, "Cognitive Development of Partner Robots Based on Interaction with People", Proc. (CD-ROM) of Joint 4th International Conference on Soft Computing and Intelligent Systems and International Symposium on Advanced Intelligent Systems, [6] W. Gerstner, Spiking Neurons, In W. Maass and C. M. Bishop, editors, Pulsed Neural Networks, chapter 1, MIT Press, 1999, pp [7] W. Gerstner, W. M. Kistler, Spiking Neuron Models, Cambridge University Press, [8] H.-P. Schwefel, Numerical Optimization of Computer Models, John Wiley & Sons, New York, [9] G. Syswerda, A Study of Reproduction in Generational and Steady- State Genetic Algorithms, In Foundations of Genetic Algorithms, Morgan Kaufmann Publishers, Inc., pp ,

26 A Survey of Intelligent Tutoring and Affect Recognition for Mobile Devices Malinka Ivanova Technical University of Sofia Abstract: Intelligent tutoring is used to support a student through arrangements of adaptable learning paths. Some of intelligent tutoring systems are only interested in the cognitive state of a student; others combine the cognitive state with the affective situation to achieve the best efficacy in learning. Emotional mood could be recognized through one technique or combination of several methods. The aim of the paper is to explore the specificity of intelligent tutoring improved by emotions recognition and suitable for use on mobile devices. This will facilitate educators in their intention to realize mobile intelligent tutors. Keywords: intelligent tutoring, affect recognition, facial expression recognition, mobile devices, mobile learning 1. INTRODUCTION The role of an intelligent tutor is to support learning of a student according to his individual specific characteristics and level of knowledge in a given domain. Intelligent tutors are used in several pedagogical scenarios like: problem solving, ensuring step-by-step guidance considering the way of student s thinking, learning by dialog, others, providing flexible learning paths. Their construction typically consists of four modules: expert knowledge module that describes knowledge in a given subject-matter domain; student model module contains information about student background, behavior, achievement; tutoring module includes pedagogical strategies and instruction to students, and user interface module that ensures a flexible and interactive connection between the student and the computer tutor. Nowadays the construction of intelligent tutors is extended with modules for motivation improvement and student affect recognition. The reason for that is research showing that emotional state influences on learning, decision making and problem solving. Different techniques for affect recognition are implemented including: facial expression recognition, analysis of voice characteristics, analysis of text typing dynamics, self-evaluation via 26

27 Computer Systems and Engineering emotional quiz, measuring the pressure on the chair, measuring the heart rhythms, etc. An intelligent tutoring system (ITS) can utilize one of these techniques or combination of several of them to receive needed information about the emotional state of a student. Recently, researchers have been working intensively on Internet faster applications and ITSs mobile versions. This is dictated by the lifestyle of young people and advances in mobile technologies. Also, the problems of delay of signal in wireless networks and standardization are explored in [9], [10], [11] and it is proved that the signal delay is relatively small. Anyway, the created mobile versions of ITSs are a few with limited features. The aim of this research is to recognize the main usage of mobile devices for learning, to figure the specific characteristics in design of mobile learning environments, to understand the face and facial expression recognition and its implementation in mobile devices in context of ITSs improvement. The explored provision of scientific achievements in the areas of ITSs, mobile technologies, learning design, and affect recognition will facilitate educators in their intention to put in practice mobile intelligent tutors. 2. MOBILE INTELLIGENT ENVIRONMENTS The utilization of mobile technologies for ensuring an effective tutoring support and the tutor s role and tasks in mobile learning settings are discussed in [8]. Several tutoring methods are suggested after summarization of face-to-face classroom practice and elearning instructional strategies. The theoretically built model Activation, Externalization, Focusing, Interpretations, Reflection and Information Processing (AEFIRIP) by Silander and Rytkönen, reflecting the specificity of mobile tutoring and learning is examined as a main pedagogical statement for implementation of a semiautomatic tool that facilitate mobile tutoring. The educational practices suitable for usage in mobile variant are classified in seven categories: (1) tutoring and guidance through sending sms, s for help providing, writing in blogs, performing inquiry, tutoring by video phone calls, keeping tutoring dialogue, gathering the students answers after learning tasks doing, gathering artefacts by students; (2) receiving students products, chat, one-to-many communication; (3) communication through real-time interaction, access to student s portfolio, access to students achievements; (4) evaluation / assessment through the results after tasks doing in specific learning situations; (5) positioning of students through pedagogical strategies that incorporate in themselves the possibilities of GPS; (6) simulation through access to simulators, examples, instructional games, demos, videos. A detailed study about the performed informal learning activities in time of mobile devices usage shows that the main interactions are related to the exploitation of the mobile, connective and collaborative functionalities of 27

28 these devices [4]. The findings point that learners perform a wide variety of intentional and unintentional learning activities using mobile learning applications grouped in seven categories according to the functional architecture of Patten, Arnedillo Sanchez, and Tangney: (1) collaborative activities information sharing and uploading through wiki, blog, forum, and sms, skype VoIP; (2) location aware activities using GPS, downloading contextual information; (3) data collection activities - recording audio notes, writing text, taking picture and video; (4) referential activities looking for information to dictionaries, translators, e-books, course materials; (5) administrative activities organizing calendar events and contacts; (6) interactive activities related to applications with information input and output in support of learning; (7) microworld applications (learning scenarios from the real practice) are not used in informal learning context. 3. DESIGN OF MOBILE ENVIRONMENTS Koole and Ally are developed a theoretical model FRAME (Framework for the Rational Analysis of Mobile Education) that examines the processes in mobile learning and proposes a specification of strategies for mobile teaching and learning [12]. The model renders the reciprocal actions among mobile technologies, learner capabilities and socio-cultural background and guides the designers of mobile learning in their preparation of a mobile educational environment. They give prescriptions about design of: (1) learning content in form of learning objects for flexible lessons delivery, served according to the cognitive level of a given student and leading to the successful achievement of learning goals; (2) learning activities considering the different students styles of learning and the different needs for instructional support; (3) teaching instructions that facilitate the mental processing, stimulate the attention and maintain the motivation, including sequences of instructions forcing students to apply their existing knowledge in problem solving or in real life situations, to analyze, to synthesize new knowledge, to evaluate, ensuring deep learning and storage in the long-term memory. The authors conclude that the focus in the design of a mobile learning environment has to be put on the knowledge navigation paradigm where the tutor plays a crucial role in assistance providing at selection and manipulation of prior information. 4. ITS FOR MOBILE DEVICES A mobile version of a typical ITS designed according to the characteristics of mobile devises is presented in [2]. A geometry tutor from Carnegie Learning framework is used as bases for experimentation. This math tutor is 28

29 Computer Systems and Engineering converted in the so called Poor Man s Eye Trackers tutor in order for the user interfaces to be evaluated. Its interface is divided into several regions and every one of them is covered by an opaque layer which is removed through a mouse click by a student. In this way during the solving geometric problems, the students can work only with one region at a time. The intelligent tutor records the opened regions, the transition flows between regions and the time spent for each one student. The received data is analyzed and the regions with lower usage are re-designed in tabs. Authors consider that such solution will activate students for frequent usage of the converted in tabs regions. Chen and Hsu present a solution of a personalized intelligent mobile system for improving English reading ability that consists of a mobile client application of English learning system, a remote server and an agent for data synchronization between client and server [3]. The results after experimentation point to several benefits of the proposed mobile system for learners like: reduction of cognitive overload because of the personal recommendation for English articles reading, promotion of English learning, comprehension and reading. 5. FACIAL EXPRESSION RECOGNITION The face characteristics and its muscle motions are described with a set of parameters which is utilized for recognition of facial emotions. Several sets with such parameters are created, but the most used are the following two: the Facial Action Coding System (FACS) presented by Ekman and Friesen [7] and the set with Facial Animation parameters (FAPs) which is included the MPEG4 Synthetic/Natural Hybrid Coding (SNHC) standard. Anyway, the MPEG4 standard does not give information about some facial behavioural characteristics that differentiate the posed from spontaneous emotions. MPEG4 is applied for preparing animations of facial avatars, but it does not count the changes in surface texture like shape changes, bulges and wrinkles that are important for FACS action units description. The differences between posed and spontaneous expressions are rooted in emotions appearance and their temporal characteristics (onset-apexoffset). Posed and spontaneous expressions can be recognized by the movement of given facial components and by their movement dynamics. Ekman talks also about micro facial expressions and squelched expressions [6]. Micro facial expressions are observed in the cases when people are trying to mask their real emotions. Their duration is very short about 1/25-1/15of a second, but they are complete expressions (they have onset, apex and offset). The squelched expressions begin their showing but they are immediately stopped and changed to other expression. The squelched expressions are uncompleted and their duration is longer than micro expres- 29

30 sions. At this moment several automatic recognition systems for micro expressions are developed, but still the meaning of micro facial expressions for educational society are not researched. Instead of that there are a wide range of good practices at implementation of facial expression recognition systems working with posed and spontaneous expressions, including in the area of ITSs. 6. FACE RECOGNITION IN MOBILE DEVICES A face recognition system for Motorola DROID phone is presented in [5] that has been developed after investigation and experimentation with several algorithms for colour segmentation and face detection. The findings point to the existence of limitations related to the incorrectness at color recognition, templates dependence, not good detection of people s faces from different ethnic groups. Other two algorithms Eigenface and Fisherface for face recognition are tested and the resulted rate for correct recognition is 84.3% for Eigenface and 94.0% for Fisherface. Anand et al. report for a desktop application of ebook reader implementation with possibilities for facial expression recognition [1]. Several functions related to the display control can be manipulated by the facial expression. For example, when a person is frowning the UI will be changed, if his eyes are opened wide then the content is zooming out, if the head is nodded in right or in left, then the previews or next page will be turned, if the finger is on mouth then the audio will be muted. For facial expression recognition FACS is used in two phases facial action units detection and inference of the output emotion based on detected active units. Other methods like Gabor filter, AdaBoost and Support Vector Machine are applied too. Authors are working on adaptation of this system to Android tablet device. 7. CONCLUSIONS Intelligent tutoring for mobile devices makes its first progressive steps for ensuring high quality of learning giving ubiquitous access to knowledge when students are outside of classrooms (for example, distance education, informal learning). At the beginning stage are also applications combining the level of cognition and affective state of a student to provide appropriate learning object or path. There are several problems related to the design of new applications (media form, duration of learning objects, attention allocation, emotions recognition) and adaptation of the existing desktop or webbased tutors to mobile versions. Further research is needed to outline the effective pedagogical strategies, cognitive issues and technical solutions. 30

31 Computer Systems and Engineering 8. REFERENCES [1] Anand, B. et al. (2012) Beyond Touch: Natural Interactions Using Facial Expressions, The 9th Annual IEEE Consumer Communications and Networking Conference Special Session Affective Computing for Future Consumer Electronics, pp , [2] Brown, Q. et al. (2008) The design of a mobile intelligent tutoring system, In Proceedings of the 9th International Conference on Intelligent Tutoring Systems 2008, https://www.cs.drexel.edu/~salvucci/publications/brown-its08b.pdf [3] Chen, C. M., Hsu, S. H. (2008) Personalized Intelligent Mobile Learning System for Supporting Effective English Learning. Educational Technology & Society 2008, 11 (3), pp [4] Clough, G. et al. (2009) Informal Learning Evidence in Online Communities of Mobile Device Enthusiasts, Mobile Learning: Transforming the Delivery of Education and Training, Issues in Distance Education, Athabasca University Press, pp [5] Dave, G. et al. (2010) Face Recognition in Mobile Phones, a_davo_chao_facerecognition.pdf [6] Ekman, P. (2003) Darwin, Deception, and Facial Expression. Annals of the New York Academy of Sciences, vol. 100, pp , [7] Ekman, P., Friesen, W. (1978) Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto, CA. [8] Graham, K. (2010) The use of mobile communication technology for tutoring, [9] Hristov, V. (2009) Signaling Delay in Wireless Networks with Session Initiation Protocol over User Datagram Protocol, Proc. of the Conference FMNS 09, Blagoevgrad, 3-6 June, vol. 1, pp [10] Hristov, V. (2009) Signaling Delay Using Session Initiation Protocol over Transmission Control Protocol in Wireless Networks, Proc. of the International Conference on Information Technologies (InfoTech-2009), September 17-20, 2009, Varna St. St. Constantine and Elena, Bulgaria, pp [11] Hristov, V. (2010) Session Initiation Protocol Interworking with Traditional Telephony and Signaling Delay Introduced by Internet, Proc. of the International Conference on Information Technologies (InfoTech-2010), September 16-17, Varna, Bulgaria, pp

32 [12] Koole, M., Ally, M. (2006) Framework for the Rational Analysis of Mobile Education (FRAME) Model: Revising the ABCs of Educational Practices, auspace.athabascau.ca/bitstream/2149/612/1/ pdf 32

33 Computer Systems and Engineering FPGA Based Mixed-Signal Circuit Novel Testing Techniques Sotirios Pouros *, Vassilios Vassios *, Dimitrios Papakostas *, Valentin Hristov ** *1 Alexander Technological & Educational Institute of Thessaloniki, Greece ** South-West University, Blagoevgrad, Bulgaria Abstract: Electronic circuits fault detection techniques, especially on modern mixed-signal circuits, are evolved and customized around the world to meet the industry needs. The paper presents techniques used on fault detection in mixed signal circuits. Moreover, the paper involves standardized methods, along with current innovations for external testing like Design for Testability (DfT) and Built In Self Test (BIST) systems. Finally, the research team introduces a circuit implementation scheme using FPGA. Keywords: Fault Detection, Mixed Circuits, BIST, DfT 1. INTRODUCTION Using fault detection techniques on electronic component/devices, manufacturers can enhance the good, reliable quality and operation of their respected products before shipping the products to their potential customers and speeds up the fault diagnosis in components/devices which leads to a faster repair of the faulty component and ultimately less down time for the device/machine that uses these component/devices.[1-4] Current research projects have also adapted the use of the power supply current IPS for producing a good/fault signature and a reference metric good/fault classification. [5-11] Several fault testing methods and techniques are utilizing both the static and the mixed signal specifications of mixed signal circuits such as ADC s and DAC s to produce a good/fault signature/metric for comparison. A summary of these specifications and the related work will be presented. Finally, a circuit implementation scheme using FPGAs will be proposed. 1 This research has been co-financed by the European Union (European Social Fund ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III. Investing in knowledge society through the European Social Fund. 33

34 2. METHODOLOGY TESTING SPECIFICATIONS The testing specifications are presented in the following paragraphs. Mixed signal IC s, such as ADC s and DAC s have static and dynamic specifications which are used by researchers in order to produce the good/fault signature and/or the classification metric. A complete set of these specifications can be found also in the data books of different manufacturers. The main static and dynamic specifications will be described below. The specifications to be described are: Static: Differential Non Linearity (DNL),Integral Non Linearity (INL), Gain-Offset Error Dynamic: Configurable Logic Blocks (CLB), Signal to noise ratio (SNR), Total Harmonic Distortion (THD), Signal to noise and Distortion ratio (SINAD), Effective Number of bits (ENOB) Static Specifications Differential Non Linearity (DNL), is the maximum deviation between two neighboring codes. Ideally, a change of one LSB in digital code corresponds to one LSB analog voltage signal change for DAC s and vice versa for ADC s [3]. Integral Non Linearity is defined as the maximum deviation of the ADC/DAC transfer function of a straight line from start to end point. Two main methods are used, the end point method and the best straight line method. Gain-Offset Error is the transfer function of a DAC/ADC which can be expressed from the function D=GA+K where D is the Digital code, A the Analog signal value and K, G are the offset and the gain respectively (K, G are constants). The Gain Error is the deviation between the theoretical value of G (given by the manufacturer) and the actual value of the device expressed as a percentage difference between the values. It can also be expressed in mv or LSB s Dynamic Specifications Signal to noise ratio (SNR) is the ratio of the rms signal amplitude without the 5 first harmonics over the mean value of the square root sum of all other spectral components except the DC component. Total Harmonic Distortion (THD) is defined as the ratio of the rms value of the primary frequency over the mean value of the root sum squares of its harmonics Signal to Noise and Distortion Ratio (SINAD) is the ratio of the rms signal amplitude, including the 5 first harmonics, over the mean

35 Computer Systems and Engineering value of the root sum square of all other spectral components without the DC component. Effective Number of bits (ENOB) is defined by the following equation (1): sin AD 1 (1) ENOB = 6,02 There are more static and dynamic specifications for ADC s and DAC s but the above mentioned specifications were widely used by researchers to extract their respective metric [1,2,4]. 3. TESTING METHODS The testing methods to be described are the following: 3.1. Basic testing method The emerged Build In Self Test (BIST) technique partially solves the issue of a complex testing scheme, since it is integrated inside the component at hand. BIST can significantly reduce the production cost but can be impractical in many cases due to the fact that the BIST is more complex than the tested component or/and it occupies a large area inside the component.[1] All the methods rely on the basic concept behind these testing schemes which is the comparison of the output response (signature) of the nonfaulty Circuit Under Test (CUT) to the faulty one. The output voltage of a good CUT s VOUT provides the signature against which the signatures of the faulty ones will be compared and classified according to the respective match. If the signatures match the CUT then it is classified as good and if the signatures don t match then the CUT s are classified as faulty [5]. A signature provided by measuring the power supply current IPS [6] gave a new interesting aspect to the ongoing research Input Stimulus Different input signals and patterns are used for driving the CUT in order to produce the output signature. These signals, range from pure sinusoidal [7] to more complex signals such as multitone signals [8], impulse response [9] and pseudo-random patterns [10]. In some schemes there is no direct input signal but a positive or negative feedback from the output which drives the CUT to oscillate (Oscillation BIST) [11]. 35

36 3.3. Classification methods The output response or/and the IPS waveform from a series of CUTs measurements/simulations (signature) will compose a data base which will be the basis of the good/faulty classification. The respective signature of the good CUT will be compared to the signature of the Device Under Test (DUT) and will be classified accordingly. In order to classify the DUTs, a metric is used which derives from the spectral analysis [12], RMS and the mean value of the signature [13]. SNR, SINAD, THD [14] and other mixed signal static and dynamic specifications are also used to produce the classification metric. At start, the Euclid distance was used to compare the signatures. Current implementations introduced the wavelet packet spectral analysis [15], the Malahanobis distance [16],[17] and the Voltera series [9] as a classification metric. 4. CONCLUSIONS FUTURE WORK This paper provides the foundations of the future work and it will guide the selection of the method to be implemented. The aim is to develop external testing devices which will take the current signatures of positive, negative and ground power supply lines of the DUT and classify the DUT accordingly. The IPS of the CUT (positive, negative power supply lines and ground line) will be sampled by an external Analog to Digital Converter to the FPGA. The sampled data are led to a Digital Filter, positioned into the Signal Processing Unit, located inside the FPGA and used for antiallizing and denoising purposes. After the filtering, the sampled data are led to the second stage of the signal processing unit also located inside the FPGA, At this stage, the signal processing unit will perform the spectral analysis of the IPS signature using Fast Fourier Transformation (FFT) and Discrete Wavelet Transformation (DWT) algorithm to extract the energy of the signature. The rms and mean values of the IPS signature will be also calculated in the same unit. All these features will provide the necessary information to create a signature data base for comparing the good circuits against the measured CUTs for the good/fault classification. The comparison will be executed after the CUT s signature is extracted. Both signatures, good and the DUT s will be compared with the help of a distance metric. The Malahanobis distance metric may be used, which is similar to the Euclid distance metric but more efficient as an algorithm. This comparison will lead to a good/fault classification. 36

37 Computer Systems and Engineering Fig. 1: Block Diagram of our future implementations. The novelty that will be introduced is the Digital Stimulus Pattern Generator incorporated inside the FPGA. Its purpose is to apply the correct digital or analog signal (after a D/A conversion) to the CUT according to the specification of the CUT. When a CUT cannot be classified from the signature taken for a specific stimulus, then the pattern generator will create a new stimulus that will provide a new signature for comparison. This stimulus will be created by LUT s, DDS and LFSR. The Stimulus will be also user selectable depending on the CUT. The A/D conversion of the current sampling and the D/A conversion for the CUT stimulus will be done externally and all the digital processing, filtering, frequency component analysis, metric extraction and final good/faulty classification will be implemented inside the FPGA. FPGA s can be significantly faster than any conventional DSP and they have parallel processing capabilities which can be very useful in simultaneous processing algorithms. 37

38 5. REFERENCES [1] Lee D., Yoo K., Kim K., Han G., Kang S., (2004), Code-Width Testing-Based Compact ADC BIST Circuit. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II: EXPRESS BRIEFS, VOL. 51, NO. 1. [2] Olleta B.,Jiang H., Chen D., Geiger R., (2009), Methods of testing analog and mixed signal using dynamic element matching for source linearization, US Patent Number: B2. [3] Maxim Integrated, INL/DNL Measurements for High-Speed Analogto-Digital Converters (ADCs), Available: (accessed February 20, 2013) [4] Kester W., Bryant J., Sampled Data Systems Available: MixedSignal_Sect2.pdf (accessed February 20, 2013) [5] Stroud C., (2002), A Designer s Guide to Build-In Self Test, New York: Kluwer Academic Publisher. [6] Bell I., Sprinks S., Dasilva J., (1996), Supply current test of analog and mixed-signal circuits, Proc. Inst. Elect. Eng.-Circuits Devices Syst., vol.143,no 6, pp [7] Park J., Abraham J., (2008), Parallel Loopback Test of Mixed- Signal Circuits, Proc IEEE VLSI Test Symposium. [8] Sindia S., Singh V., Agrawal V., (2009), Multi-Tone Testing of Linear and Nonlinear AnalogCircuits using Polynomial Coefficients, Proc. Asian Test Symposium. [9] Park J., Chung J., Abraham J., (2009), LFSR-based performance chartacterizartion of nonlinear analog and mixed signal circuits, Proc. Asian Test Symposium. [10] Marzocca C., Corsi F., (2002), Mixed-Signal Circuit Classification in a Pseudo-Random Testing Scheme, Journal of ElectronicTesting:Theory and Applications 18, [11] Arabi K., Kaminska B., (1997), Efficient and Accurate Testing of Analog-to-Digital Converters Using Oscillation-Test Method, ED&CT 97. [12] Dimopoulos M., Spyronasios A., Papakostas D., Konstantinou D., Hatzopoulos A., (2010), Circuit implementation of a supply current spectrum test method, IEEE Trans.Instrum.Meas., vol. 59, no,. 10, pp [13] Zwolinski M., Chalk C., Wilkins R., Suparjo S., (1996), Analogue Circuit Test using RMS Supply Current Monitoring. [14] Toner M., Roberts G., (1993), A BIST scheme for an SNR test of a sigma-delta ADC, IEEE Int. Proc. Test. Conference 38

39 Computer Systems and Engineering [15] Dimopoulos M., Spyronasios A., Papakostas D., Hatzopoulos A., (2010), Wavelet energy-based testing using supply current measurements, IET Sci., Meas. Tech., vol. 4, no. 2, pp [16] Dimopoulos M., Spyronasios A., Hatzopoulos A., (2011), Wavelet analysis for the detection of parametric and catastrophic faults in mixed-signal circuits, IEEE Trans. Inst. Meas. vol. 60, no. 6. [17] Kalpana P., Gunavathi K., (2007), A novel implicit parametric fault detection method for analog mixed signal circuits using wavelets ICGST-PDCS Journal, vol. 7,Issue.1. 39

40 Vulnerability issues on research in WLAN encryption algorithms WEP WPA/WPA2 Personal Lazaridis Ioannis, Pouros Sotirios, Veloudis Simeon DEI College, Thessaloniki, Greece Abstract: This paper presents historic and new evidence that wireless encryption algorithms can be cracked or even bypassed which has been proved by other researchers. The paper presents a description of how WEP and WPA/WPA2 Personal encrypt data and how the passphrase is shared between the nodes of the network. Modern tools available on the internet have been evaluated, decomposed and tested to provide evidence on the reliability of passwords. A number of criteria are used to compare the tools and their efficiency. Keywords: WLAN, security algorithms, encryption methods, passphrases, Backtrack, cracking tools 1. INTRODUCTION A wireless LAN (WLAN) is a network in which a user can connect to a local area network (LAN) through a wireless connection. Since most modern WLANs are based on IEEE standards the term Wi-Fi is used as a synonym for WLAN. Nowadays, WLAN devices are commonly used by everyone, mostly because of the need to connect to the Internet. [1] At home, at work, even public places such as local café and shopping centers people are able to connect to the Internet via a Wi-Fi device connected to a Wi-Fi Access Point (AP).[2] The issue here is that almost nobody actually cares if the connection just established is safe or not. Most people have heard the terms authentication, encryption, WEP, WPA and WPA2 but only few knows how they work and even fewer knows how they can be cracked or even bypassed WEP In WEP authentication a wireless device sends an authentication request to the access point which will reply with a 128 bit challenge in a clear text.[3] The client will sign that challenge with the shared secret key and send it back to the access point. The AP will decrypt the signed message (uses the same shared key as client did) and verifies the challenge sent. If the challenge matches, then the authentication has

41 Computer Systems and Engineering succeeded and the client is able to access the WLAN. It must be noted that the same key is used for authentication and encryption so this kind of authentication is prone to man in the middle attacks (There is no way to distinguish if the subsequent messages are from a legitimate client or an impostor). The encryption process between an AP and a client WEP uses RC4 stream cipher. WEP uses 8-bit RC4 and operates on 8-bit values by creating an array with 256 8bit values for a lookup table. WEP also uses CRC (Cyclic Redundancy check) for data integrity. It performs a CRC checksum on the plaintext and generates a CRC value. Then that value is concatenated to the plaintext, thesecret key is concatenated to the Initialization Vector (IV) and given into therc4. RC4 creates a keystream that is based on the secret key and the IV. The keystream and the CRC+plaintext message are XOR ed. The result of that is called ciphertext. The same IV that was initiallyused is presented in clear text to the resultant ciphertext. The IV plus the ciphertext along with the frame headers are then transmitted over the air WPA WPA includes dynamic key generation, an improved RC4 data encryption that uses TKIP and 802.1x authentication.[4] It can provide data protecting and ensure that only authorized users can access the WLAN. At this point, the importance of TKIP must be stated since it employs a prepacket key, meaning that it automatically generates a new key (128 bit) for every packet. This means that static key attacks can not affect WPA. WPA has also replaced the cyclic redundancy check (CRC) that WEP uses as an integrity check since it didn t provide a strong data integrity guarantee. The integrity check algorithm used is called Michael or MIC which is stronger that CRC but as past researches has shown MIC has a flow because of its limitation to retrieve the keystream from short packets to use for re-injection or even spoofing. TKIP uses a master key which is distributed using 802.1x or PSK (in that case it derives a pairwise master key). Pairwise master key is used in order to get four other keys. These keys are used during the encryption. One of these four keys is called temporal key which is used to encrypt data over the WLAN. The temporal key is XORed with the MAC of the transmitter and then is mixed with a sequence number in order to produce a key that is used as input to the previous WEP algorithm. [5] It must be noted that by adding all these steps, the key becomes much more secure since now it depends on time and the transmitter s MAC. The source and the destination addresses are added along with the sequence number.msdu stands for MAC Service Data Unit and MPDU stands for MAC Protocol Data Unit. 41

42 1.3. WPA2 Authentication in WPA2 is performed between the client and the access point by generating a 256-bit PSK from a plaintext passphrase (8-63 characters long).[6] The PSK in conjunction with the SSID and the SSID length form a mathematical basis for the PMK (Pair-wise Master key) to be used in key generation. In order to generate the key, there is a need of two handshakes, a four way handshake for PTK, GTK derivation and a group key handshake for GTK renewal. SinceWPA2encryption is compatible with TKIP and AES we will focus on AES. [7] For AES, the MIC is calculated using a 128-bit IV. The IV is encrypted with AES and TK in order to produce a 128-bit result. This result is XORed with the next 128 bits of data. The result of that XOR is then passed through the first two steps until all 128 blocks in the payload are exhausted (AES uses groups of bits of a fixed length called blocks). Finally the first 64 bits are used to produce the MIC.Since the MIC is created the counter mode algorithm encrypts the data and the MIC. It begins with a 128-bit counter preload similar to the MIC IV, but it uses a counter value initialised to one, instead of a data length resulting in another counter used to encrypt every single packet. In order to encrypt the data and the MIC,the counter has to be initialised (if it is the first time) otherwise the counter has to be incremented. Then, the first 128 bits are encrypted by using AES and TK in order to produce a 128-bit result. A XOR is performed on that result which is going to be used later. The first 128 bits of data produce the first encrypted block (128-bit). The same procedure is repeated until all 128-bit blocks have been encrypted. Then the counter is set to zero and it is encrypted using AES and XOR with MIC appending the result the encrypted frame. 2. METHODOLOGY Technical Specifications: Machine used:samsung RV515 Processor: AMD Dual Core Processor E-450 (1.65GHz, 1MB L2 Cache) Memory: 4GB DDR3 System Memory at 1066MHz (4GB x 1) Graphics Adapter: AMD Radeon HD6470M 42

43 Computer Systems and Engineering NIC: Alfa AWUS036H 5 db Antenna [11]O/S: Backtrack 5 R WEP Tab.1: RAM consumption in standby during injection and cracking. RAM/standby RAM/injection RAM/cracking FERN 150 MB 840 MB 1.2 GB Gerix MB 178 MB 198 MB Airdump-ng MB 146 MB 148 MB Tab. 2: CPU consumption in standby during injection and cracking. CPU/standby CPU/injection CPU/Cracking FERN 30.6%-20.3% 100% x2 100% x2 Gerix 11.1%-24.6% 36.7%-50.0% 72.2%-99.9% Airdump-ng 9.7%-25% 71.2% % 48.5%- 30.0% WEP encryption: 64 bit Passphrase: Tab. 3: Time and IVs needed in order to crack the password. Time to decrypt IVs needed FERN 00:22,0 18,500 Gerix 00:20,6 8,500 Airdump-ng 00:14,5 8,000 Passphrase: Tab. 4: Time and IVs needed in order to crack the password. Time to decrypt/12000 Ivs IVs needed FERN 01:01,6 14,700 Gerix 02:02,6 11,000 Airdump-ng 01:57,1 11,900 43

44 WEP encryption: 128 bit Passphrase: Tab. 5: Time and IVs needed in order to crack the password. Time to decrypt/12000 Ivs IVs needed FERN 04:24, Gerix 03:10,5 39,200 Airdump-ng 03:03,2 32,500 Three tools were used to grab and replay ARP packets into the network. [8] This cause the network to send ARP replay packets, thus increasing the number of packets sent. After that WEP key was cracked by analysing cryptographic weaknesses in the packets that I have sniffed (the ARP packets) WPA Tab. 6: RAM and CPU consumption while cracking. RAM/cracking CPU/Cracking FERN 320 MB 100% 40% Gerix 218 MB 100%-38% Airdump-ng 204 MB 100%- 38% Tab. 7: Time required to find the passphrase (Zealotsk) which is at the end of the dictionary. Time to find the passphrase FERN 00:53,6 Gerix 00:52,1 Airdump-ng 00:52,0 Tab. 8: Time to find the passphrase (Zealotsk) which is at the middle of the dictionary. Time to find the passphrase FERN 00:33.6 Gerix 00:34,2 Airdump-ng 00:33,3 44

45 Computer Systems and Engineering A dictionary attack was performed, using the same three tools as WEP. The dictionary list used contains movie characters and 26,707 words. For the first test the last word of the dictionarywas chosen which was zealotsk (The sk was added at the end since at least 8 characters were required). For the second test the same word had been placed right at the middle of the list (position: 13353). [9] It must be mentioned that all of the tools were able to grab the WPA handshake in a matter of seconds (5-10) but it is not something that it can be measured precisely since it was always random. It is really important to understand that all these tools do not actually crack WPA, but they crack the WPA handshake protocol. Finally, these tools are able to use both.txt.lst files WPA2 Tab. 9: CPU consumption in standby during injection and cracking. RAM/cracking CPU/Cracking Reaver 531 MB 100% 100% Tab.10: Time needed to crack PIN in seconds, minutes and hours. Seconds to crack the PIN Minutes to crack the PIN Hours to crack the PIN Since a Dictionary attack was already demonstrated for WPA, it was decided that another tool is going to be used which is called Reaver. [10] The main concept is to brute-force attack the AP itself, attempting every single possible combination in order to find the AP s 8 digit PIN number and get all the credentials of the AP. This makes it a lot of easier than a simple brute force attack, in case a dictionary attack is useless, since AP s WPS pin uses only numeric characters. This means 10^8 (100,000,000) possible combinations, but since the last digit of the pin is a checksum value, which can be calculated based on the previous 7 digits, that key length is reduced to 10^7 (10,000,000) possible values. It took 8.8 hours to crack the PIN and get the passphrase. Based on an [12] online password calculator a simple brute force attack in a complex passphrase of 8 characters would take approximately years. Finally, we have to realise that even if the passphrase is changed by a legitimate user we are able to find it once again but now without waiting 5 to 10 hours since we have the PIN number. A test was performed every time the passphrase was changed, but after 4 seconds the reaver tool was able to find the new passphrase since the PIN number was applied to it. 45

46 3. CONCLUSIONS This research has proven that even with a low processing power and free software, it is possible for someone to bypass/crack every security protocol in matter of hours or even minutes. The latest security protocol (WPA2) was introduced back in 2004; it is obvious that wireless LAN is not as safe as they are supposed to be since the security mechanisms they use are out of date. 4. REFERENCES [1] Pahlavan, Kaveh; Krishnamurthy, Prashant (2009). Networking Fundamentals Wide, Local and Personal Area Communications. Wiley. [2] Wale Soyinka, (2010) Wireless Network Administration. USA: McGraw-Hill [3] WIFI-Fi Alliance: Organization. Official industry association web site. [4] SA Standards Board. Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. Communications Magazine, IEEE, 2007 [5] Ciampa, Mark (2006). CWNA Guide to Wireless LANS. Networking. Thomson [6] Wolter Lemstra, Vic Hayes, John Groenewegen, (2010)The Innovation Journey of Wi-Fi: The Road To Global Success, Cambridge University Press) [7] Bulk, Frank.(27/1/2006) Learn the basics of WPA2 Wi-Fi security. Network Computing (accessed March 18, 2013) [8] Vivek Ramachandran, (2011) Backtrack 5 Wireless Penetration Testing. Birmingham, UK: Pactk Publishing Ltd. [9] Viehbock, Stefan (26 December 2011). Brute forcing Wi-Fi Protected Setup [10] Reaver tool website - (accessed March 18,2013) [11] BackTrack Linux Penetration Testing Distribution (accessed March 18, 2013) [12] Password Calculator - (accessed March 18, 2013) 46

47 Computer Systems and Engineering Experimental studies of the web server defenses against TCP SYN Flood attacks Nina Sinyagina, Stela Ruseva Faculty of Mathematics and Informatics Sofia University St. Kliment Ohridski Abstract: DDoS attacks are accomplished by the combined actions of variety of program components available on Internet hosts. A system for protecting against DDoS attacks was developed. DDoS attacks launched by SYN floods can be very problematic for servers that are not properly configured to handle them. A system for protection Ruslan has been developed, aiming at overcoming the DDoS attacks. It changes parameters of the OS core and basic configuration files. The system contains additional modules. It has a stable performance under real conditions - DDoS attacks. Its ability to keep the performance of the web server has been proved. A survey of the problem and the long-term mechanisms of defense against attacks was made. Keywords: Network Security, Distributed Denial of Service (DDoS) attack, defense system. 1. DESCRIPTION OF THE PRОBLEM The attack leading to the impossilbility to get information or to get computer systems function without being overlodded is called DoS - (Denial of Service). This kind of attack hamper or fully block the leagal users responses to services. A protective system, aiming at defending a web server against DDoS attacks has been developed. The system changes some parametres of the OS as well as basic configuration files and contains additional modules. Basic elements of the protective Ruslan system are the parametres of the OS core, the TCP/IP stack and the script[1-4] for iptables. The configuration of the HTTP server used for the study is: Processor: Intel Core i CPU, 3.30 GHz, 3M Cache Processor speed: 3.30 GHz RAM memory: 8 GB 47

48 Network adapter: 3Com Typhoon (3CR990-TX-97) at MMIO 0xecf80000, 00:01:03:e6:65:e9 OS: CentOS Linux release 6.0 ; Linux version el6.i686 gcc version Fig. 1: Ruslan protective system against DDoS attacks. The following command shows the default parametres of the TCP/IP stack variables as well as those of the netfilter (standart network filter for OS GNU/Linux): cat /etc/sysctl.conf The size of the table for the number of simultaneous connections through: net.ipv4.netfilter.ip_conntrack_max = The protection against arp table overflowof the network interface (Neighbour table overflow): net.ipv4.neigh.default.gc_thresh1 = 2048 net.ipv4.neigh.default.gc_thresh2 = 4096 net.ipv4.neigh.default.gc_thresh3 = 8192 net.ipv4.tcp_mtu_probing = 1 Maximum number of simultaneous connections to the socket: net.core.somaxconn = 4096 TCP keepalive is virtually swtched off:

49 Computer Systems and Engineering net.ipv4.tcp_keepalive_time=1 The number of the packets keepalve which will be sent by the server before closing the connection is: net.ipv4.tcp_keepalive_probes=1 net.ipv4.tcp_keepalive_intvl = 10 Decreasing the time to refuse the connection by default is 5 days, which is too much. net.ipv4.netfilter.ip_conntrack_tcp_timeout_established = The buffer dimentions by default for receiving and sending data through sockets are set to 256 КB: net.core.rmem_default = net.core.wmem_default = Maximum size of packet backlocks: net.core.netdev_max_backlog = 8192 The maximum size of the TPC buffers is increased to 16МB: net.core.rmem_max = net.core.wmem_max = The minimum, standart and maximum size of the autoconfiguration limits for TCP and UDP buffers in bytes is increased: net.ipv4.tcp_rmem = net.ipv4.tcp_wmem = net.ipv4.udp_rmem_min = net.ipv4.udp_wmem_min = net.ipv4.tcp_mem = net.ipv4.udp_mem = Priority for start of swapping (from 0 to 100): vm.swappiness = 70 The backlock of the half-open connections is increased net.ipv4.tcp_max_syn_backlog=4096 The parametre tcp_synack_retries controls the numler of the retranslations[5] in ОS GNU/Linux. It is 5 by default, which means deleating of a 49

50 half-open connection in 3 minutes. The transmission is set to be realised up to the third second and the full time for saving of the half-open connections in the backlock is fixed to 9 seconds: net.ipv4.tcp_synack_retries=1 50 The timeout for FIN wait until final close of socket: net.ipv4.tcp_fin_timeout = 10 Permission to support a large scale window for TCP protocol (according to RFC1323 a highperformance protocol): net.ipv4.tcp_window_scaling = 1 Increase of the number of the accessible network ports: net.ipv4.ip_local_port_range = To avoid the peculiarities when decreasing the size of the sliding window (because of transmitting packets for a second time) for a single connection, the size of the window for all other connections with this host has to be decreased: net.ipv4.route.flush=1 Cashing of the status ssthresh (slow start threshold limit) for the other connections: net.ipv4.tcp_no_metrics_save = 1 Changing the congestion control dlgorithm: net.ipv4.tcp_congestion_control=htcp The core is set not to answer a broadcast ping. Each ICMP message, answering a broadcast or a group address is ignored. There has to be written: net.ipv4.icmp_echo_ignore_broadcasts = 1 TCP syncookies are used(against TCP SYN packet flooding): net.ipv4.tcp_syncookies = 1 To mislead programs of nmap type, which can identify a OS by the network stack characteristics, the TTL size by default of 64 has to be changed and number 128 has to be written in the file ip_default_ttl: net.ipv4. ip_default_ttl = 128 Selective acknowledgements are banned, RFC2018 (net.ipv4.tcp_sack):

51 Computer Systems and Engineering net.ipv4.tcp_sack=0 How often a connection, closed by the defender has to be killed is determined by: net.ipv4.tcp_orphan_retries=1 The rp_filter is switched on (IPsrc verification, defense against IP spoofing): net.ipv4.conf.all. rp_filter=1 Packets with impossible addresses to get logged have to be refused: net.ipv4.conf.all. log_martians =1 Protection against bogus responses to broadcast requsts written in a log file: net.ipv4.icmp_ignore_bogus_error_responses = 1 ICMP Redirect is switched off: net.ipv4.conf.all.send_redirects=0 net.ipv4.conf.all.accept_redirects=0 Routing, defined by the IPsrc source, is switched off: net.ipv4.conf.all.accept_source_route=0 Multicast dispatch support is switched off: net.ipv4.conf.all.mc_forwarding=0 2. EXPERIMENT DESCRIPTION A number of experiments have been made to evaluate the deny of service by (or without) using Ruslan protective system when flooding a a web server with TCP SYN packets. To guarantee the neatness of the experiment, a version for connection without intermediate routers has been chosen because the administrator of each intermediate router sets rules to filtrate their networks by themselves, which could influence results. In the experiment, by using a 16 port switch web server, 15 machines were connected in a local network, which were used simultaneously as attacking machines and as clients. The switch model is Cisco Linksys SR2016T-EU 16-Port 10/100/1000 Gigabit Switch (SR2016T-EU). 51

52 The 16 ports switch over at the rate of 32 Gbps. The channel capacity is 23,8 million packets per second. Configuration of hosts(clients and attacking) interacting with the HTTP server: Processor: Intel Celeron 2.00 GHz Processor speed: 2.00 GHz RAM memory: 512 MB Network asaptor: 100Mb/s Ethernet OС: CentOS Linux release 6.0; Linux version el6.i686 gcc version (Red Hat ) Fig. 2: Topology of the experimental network. The IPTraf program, which was started on the web server, is used to measure the input and output traffic in packets/ sec. The registered through IPTraf traffic трафик pulsates, so, the tables indicate average values. The computers, alleged to be attacking hosts generate TCP SYN packets, which simulate SYN flooding. A program used for the purpose sends packets to the web server without the defence of Ruslan system from a single host. The web server registers 47 thousand packets per second and manages to respond to only 11 thousand packets per second. This proves that the system has resource to respond to less than a quarter of the received requests. When two hosts attack, the resource is drained again. The system registers 32 thousand and responds to 7 thousand packets. It

53 Computer Systems and Engineering is obvious the resources are drained and this shows that there is TCP SYN flooding (DDoS attack). 3. EXPERIMENTAL RESULTS It is experimentally proved that the server fails when attacked by 7 hosts but when Ruslan is used it functions even if it is attackes by all 15 machines. Tab. 1: Generated input and output traffic at the web server without Ruslan defence system. Number of attacking machines Input traffic, packets/sec Output traffic, packets/sec Tab. 2: Generated input and output traffic at the web server with Ruslan defence system. Number of attacking machines Input traffic, packets/sec Output traffic, packets/sec

54 4. CONCLUSIONS As a result of the studies and the analysis made, there can be drawn the following conclusions: 1. An experimental evaluation has been made of the denial of service with/without the use of Ruslan defending system against DDoS attacks due to web servers flooding with TCP SYN packets. 2. The steady work of Ruslan under a real DdoS attack was experimentally proven. Its ability to keep the working capacity of the web server was confirmed. 3. Ruslan manages to keep the capacity of the web server at maximum flooding with false requests to the attacked system, related to the channel capacity and hardwere devices. Without the help of Ruslan the web server fails to serve the clients even at much lower levels of input flow of requests. 5. REFERENCES [1] CERT. TCP SYN Flooding and IP Spoofing Attacks. CERT Advisory CA [2] Ipsysctl-tutorial, Oskar Andreasson, ipsysctl- tutorial/ [3] RFC 4614 Duke, M., Braden, R., Eddy, W., Blanton, E. A Roadmap for Transmission Control Protocol (TCP) Specification Documents, 2006 [4] Slavov Z., and V. Hristov, BUILDING AN UNIVERSAL NETWORK SECURITY MODEL, Proc. of the Conference ELECTRONICS ET 2006, Sozopol, September 20-22, 2006, pp [5] V. Hristov, SIMULATION OF TRANSMISSION CONTROL PROTO- COL Proc. of the Conference SCICE 05, Sofia, 2005, pp

55 Computer Systems and Engineering Simulation of aggregation mechanism with fragments retransmission Valentin Hristov*, Bzar k. Hussan**, Firas Ibrahim***, Gergana Kalpachka* *South-west University "Neofit Rilski"- Blagoevgrad, Bulgaria **Hawler Polytechnic College "Erbil Technical Institute"-Erbil, Iraq ***University Of Tabuk- Tabuk, Kingdom Saudi Arabia, 1. INTRODUCTION Modern wireless computer networks offer more high-speed data transmission in the physical layer (PHY) and using highly efficient protocols in the Media Access Control layer (MAC)to access the communication medium. High-speed of physical layer does not lead directly to increased efficiency of the MAC layer. The reason is that increasing speed leads to faster transmission of the MAC part (in frame), but the transmission time of PHY header and the backoff time of avoiding conflicts has not decreased substantially. For example, the new n standard offers speeds up to 600 Mbps and improvements in the MAC. Transmission time of PHY header, however, is 48 µs. The maximum size of frame is limited to 7955 B. Thus, at a speed 150 Mbps, the time for transmitting user data is 424 µs, which means the proportion of transmission time for the header in frame is more than 10%. It is known that even under the best conditions, the efficiency of MAC layer (MAC_Layer_Speed/ PHY_Layer_Speed) in n fall from 42% at a speed of 54Mbps to only 10% at speed of 432Mbps [9]. Appropriate solution to overcome this phenomenon in high-speed wireless networks is the use of mechanisms for aggregating packets. Most studies of mechanisms for aggregating packets using models in which traffic has a Poisson or Bernoulli distribution. These models cannot capture the strong correlative nature of actual network traffic and the sequence of wrong packets (burst error). The aim of this paper is to propose a simulator of aggregation mechanism with fragments retransmission, taking into account time-varying radio channel characteristics and their strong relation with errors. 55

56 2. MODIFIED MECHANISM FOR AGGREGATION WITH FRAGMENTS RETRANSMISSION In the aggregation mechanism with fragment retransmission -AFR, multiple packets are aggregated into one large frame to be sent. Using technology of fragmentation, whereby if the packets are larger than a threshold, they are split into fragments that are re-transmitted in case of loss, rather than retransmitting of whole aggregated frames. In order to AFR mechanism would improve delays in aggregation in the literature [2] is proposed aggregation to do with utilization above a certain threshold. In low intensity of arrival packets in the buffer, respectively utilization (ρ =λ/µ) below this threshold, aggregation is not done, and each new arrival packet formed frame. In AFR mechanism, the MAC frame consists of a header and body (Fig. 1). All fields of the MAC header remain unchanged, only three new fields added - size of fragment, number of fragment and reserved field. The body of frame contains the headers of fragments and the bodies of fragments and control field for checking the corresponding fragment (FCS- Fragment Check Sequences). Each header fragment consists of six fields: ID of the packet (PID), length of the package (plen), start position (startpos), offset field (offset), reserved for future use fields and FCS. StartPos is used to indicate the position of body fragment in the frame and offset (offset) is used to record the position of this fragment in the packet. Fig. 1: A-AFR Frame formats. 56

57 Computer Systems and Engineering 3. SIMULATION MODEL The A-AFR mechanism and more precisely the transmitter assigns unique identifier (ID) to each fragment in the aggregated frame (Fig.1). In the receiver side fragments of a packet are concatenated according to their IDs. After the transmission of aggregated frame, constituent fragments temporarily buffered while the acknowledgement frame (ACK frame) arrives back to the transmitter. This happens with some delay (see feedback in Fig. 2). In case that a positive acknowledgment (ACK) arrives for given fragment, this fragment will be removed from the retransmission buffer (waiting buffer). If the acknowledgement arrives negative (NACK) the fragment will be transmitted again. Fig. 2: Packets transmission over wireless network. Although the transmitter sends fragments of packets in the correct order, the order of the fragments into the receiver may be broken due to the occurrence of errors, respectively retransmission. So correctly received fragments have to wait in a buffer until the lost fragments (with the missing IDs) are received correctly. The buffer for re/sequencing is located in the receiver. Once all fragments of an aggregated frame arrive, they are released from resequencing buffer (in the correct order) and packets are forwarded to the upper levels. Fig. 3 shows the various delays that fragments of packets undergo in their transmission across a wireless network using the A-AFR protocol. Total delay- Tt is the delay for packets transport, including the delivery delay- Td and the delay in the transmitter queue also called queuing delay- Tq. The delay Tt is the time elapsed since the first transmission (of fragments) of the packet until the moment in which this packet leaves resequencing buffer. The delay in the transmitter queue (Tq) is defined as the elapsed time from the arrival of packets in the buffer to the first attempt of transmission. Delivery delay (Td) includes delay of retransmission and delay of rearranging. The retransmission delay is defined as the time elapsed since the first transmission of the fragment until it successfully arrives at the receiver. Delay for rearrangement of packet fragments (resequencing delay) is equal 57

58 to the time that the packet waits until all its fragments arrive in resequencing buffer. Fig. 3: Timeline of transmission process. The generation of the input stream in the model is achieved by ON-OFF process. Modeling of time-varying radio channel is also used ON-OFF process. Fig. 4: Queuing system. In the queuing system we assume that a fragment is transmitted per slot (the time in model is slotted). The time in which an information comes for the status of the fragments of an aggregated frame (round-trip-time) is equal to m slot (Fig. 4), where m>1. This means that the available packets in the buffer are fragmented, aggregated and transmitted, but will not leave the queuing system before waiting at least m slots. 58

59 Computer Systems and Engineering The arriving of fragments of packets in the buffer of transmitter is described by: - Intensity of the arrival packets - λ. - Average number of packets in one aggregated frame p. - Average number of 128B fragments in a packet - L. The last parameter characterizes the process of fragmentation of packets, i.e. the average number of fragments aggregated in one frame is A = p.l. New arrival packet is immediately transmitted [9] only when the buffer is empty as well as there is no request for retransmission of fragment/s of earlier transmitted packet. This is because retransmission of the fragments has a higher priority than fragmentation, aggregation and transmission of newly arrived packets. The sent data from the transmitter reaches the receiver on radio channel in which there is interference which can lead to loss of fragments. In the proposed model this error prone channel is also modeled by ON-OFF generator (process with two states) and is described by parameters: - Error probability of the channel also called channel error probability- ε; - Average error burst length (length of the sequence of lost fragments due to the packet error)- B. The receiver responds with a positive or negative acknowledgment (ACK / NACK) depending on whether the fragment was received without errors or with errors. After the round-trip-time, i.e. after m slots the transmitter gets feedback (ACK/ NACK) and then starts transmission of a new aggregated frame or retransmission of lost fragment/s (for which is arrived a negative acknowledgement - NACK). Corresponding flags - bi (i = 1, 2,... m) are used to model the result of transmission in mi slot, where bi = 1 - means that the transmission of i-th fragment is not successfully and its retransmission is necessary, otherwise i.e. bi = 0 and the transmission is successfully. In the proposed model is assumed that no errors occur in transmission of acknowledgements (ACK / NACK), i.e. all acknowledgements arrive to the transmitter. General Purpose Simulation System (GPSS) has been chosen to create simulator for evolution of the A-AFR mechanism. The proposed modeling approach reflects the requirements and limitations of the GPSS language environment and accurately describes the parameters and the processes in the wireless network. 4. CONCLUSION In this paper simulation model and GPSS simulator of aggregation mechanism with fragments retransmission have been developed in order to 59

60 examine performance of the adaptive mechanism for aggregation with retransmission of fragments. 5. REFERENCES [1] N. Ghazisaidi, M. Maier and C. Assi, Fiber-Wireless (FiWi) Access Networks: A Survey, IEEE Communications Magazine, February 2009, pp [2] J. Xie and X. Wang, A Survey of Mobility Management in Hybrid Wireless Mesh Networks, IEEE Network, November/December 2008, pp [3] J. Hong and K. Sohraby, On Modeling, Analysis, and Optimization of Packet Aggregation Systems, IEEE Transactions on Communications, vol. 58, no. 2, February 2010, pp [4] L. Taneva, Intelligent Module for Data Exchange using CAN Interface, CEMA 09, 8-10 October 2009, Sofia, Proceedings p [5] R. Jain, C. So-In and A. Tamimi, Level Modeling Of IEEE e Mobile Wimax Networks: Key Issues, IEEE Wireless Communications, October 2008, pp [6] V. Hristov,, B. Tudzharov, Adaptive mechanism with aggregation and fragment retransmission for highspeed wireless networks, Bulgarian Journal of Engineering Design, No 7, February 2011, pp (in Bulgarian). 60

61 Computer Systems and Engineering Investigation of aggregation with fragments retransmission with losses in wireless networks Valentin Hristov*, Firas Ibrahim**, Bzar k. Hussan***, Kiril Slavkov**** *South-west University "Neofit Rilski"- Blagoevgrad, Bulgaria **University Of Tabuk- Tabuk, Kingdom Saudi Arabia, ***Hawler Polytechnic College "Erbil Technical Institute"-Erbil, Iraq ****Technical University of Sofia, Bulgaria 1. INTRODUCTION Modern wireless computer networks offer more high-speed data transmission in the physical layer (PHY) and using highly efficient protocols in the Media Access Control layer (MAC) to access the communication medium. High-speed wireless networks use the mechanisms for aggregating packets in order to improve efficiency of Media Access Control layer. Most studies of mechanisms for aggregating packets using models in which traffic has a Poisson or Bernoulli distribution. These models cannot capture the strong correlative nature of actual network traffic and the sequence of wrong packets (burst error). The aim of this paper is to investigate an adaptive mechanism for aggregation with fragments retransmission as examine its performance, taking into account time-varying radio channel characteristics and their strong relation with errors. 2. MECHANISM FOR AGGREGATION WITH FRAGMENTS RETRANSMISSION In the aggregation mechanism with fragment retransmission -AFR, multiple packets are aggregated into one large frame to be sent. Using technology of fragmentation, whereby if the packets are larger than a threshold, they are split into fragments that are re-transmitted in case of loss, rather than retransmitting of whole aggregated frames. In order to AFR mechanism would improve delays in aggregation in the literature [2] is proposed aggregation to do with utilization above a certain threshold. In low intensity of arrival packets in the buffer, respectively utiliza- 61

62 tion (ρ =λ/µ) below this threshold, aggregation is not done, and each new arrival packet formed frame. The A-AFR mechanism and more precisely the transmitter assigns unique identifier (ID) to each fragment in the aggregated frame In the receiver side fragments of a packet are concatenated according to their IDs. After the transmission of aggregated frame, constituent fragments temporarily buffered while the acknowledgement frame (ACK frame) arrives back to the transmitter. This happens with some delay. In case that a positive acknowledgment (ACK) arrives for given fragment, this fragment will be removed from the retransmission buffer (waiting buffer). If the acknowledgement arrives negative (NACK) the fragment will be transmitted again. The arriving of fragments of packets in the buffer of transmitter is described by: - Intensity of the arrival packets - λ. - Average number of packets in one aggregated frame p. - Average number of 128B fragments in a packet - L. The last parameter characterizes the process of fragmentation of packets, i.e. the average number of fragments aggregated in one frame is A = p.l. New arrival packet is immediately transmitted [9] only when the buffer is empty as well as there is no request for retransmission of fragment/s of earlier transmitted packet. This is because retransmission of the fragments has a higher priority than fragmentation, aggregation and transmission of newly arrived packets. The sent data from the transmitter reaches the receiver on radio channel in which there is interference which can lead to loss of fragments. In the proposed model this error prone channel is also modeled by ON-OFF generator (process with two states) and is described by parameters: - Error probability of the channel also called channel error probability- ε; - Average error burst length (length of the sequence of lost fragments due to the packet error)- B. The receiver responds with a positive or negative acknowledgment (ACK / NACK) depending on whether the fragment was received without errors or with errors. After the round-trip-time, i.e. after m slots the transmitter gets feedback (ACK/ NACK) and then starts transmission of a new aggregated frame or retransmission of lost fragment/s (for which is arrived a negative acknowledgement - NACK). Corresponding flags - bi (i = 1, 2,... m) are used to model the result of transmission in mi slot, where bi = 1 - means that the transmission of i-th fragment is not successfully and its retransmission is necessary, otherwise i.e. bi = 0 and the transmission is successfully. 62

63 Computer Systems and Engineering In the proposed model is assumed that no errors occur in transmission of acknowledgements (ACK / NACK), i.e. all acknowledgements arrive to the transmitter. General Purpose Simulation System (GPSS) has been chosen to create simulator for evolution of the A-AFR mechanism. The proposed modeling approach reflects the requirements and limitations of the GPSS language environment and accurately describes the parameters and the processes in the wireless network. 3. SIMULATION RESULTS The duration of simulations is packets, each with an average length L= 3.2 fragments (according statistics [9] for traffic in the Internet) and transfer rate λ = 150 Mbps. The values of all delays are converted to microseconds. The behavior of delays is examined versus the varying average number of fragments in aggregated frame (A), at different intensities of incoming packets (ρ =λ / µ = 0.4 and ρ = 0.6). The average errors burst length in this case is chosen to be B = 3 fragments. Figure 1 shows the delay in the queue Tq and the delivery delay Td for the given above parameters values. As one can see the delivery delay of packets-td does not change significantly when ρ and A change. The delay in the queue (of the transmitter) is increased with increasing ρ, as it is expected. The graph also shows that the delay in the queue increases with increasing parameter A. This can be explained by the fact that packets fragments arrived explosively (burst) and accumulate in the queue, which increases the value of Tq. The above means that this delay, and thus total delay can be large even at low intensity, but explosively generated fragments. Fig. 1: Average delay in queue and delivery delay, for m = 10, = 0.1, B = 3 as a function of A, with values of ρ = 0.4 and

64 The results for the delays in the transmitter queue are compared with these calculated by well-known formula W =1/(µ-λ), and as expected the differences are not greater than 20%, which is a kind of verification of proposed model. Fig.2 shows the delivery delay as a function of load -ρ (respectively, the intensity of the packets arrival) at m = 10, = 0.1, A = 2.5, and B = 3, 10, 60. Can be expected that with increasing ρ, the delay will be increased because the system becomes more and more loaded. This is correct for the queue delay, but it is not true for the delivery delay. In fact, when B is close in value to the number of slots for receiving feedback -m, i.e. channel is correlated; the delivery delay hardly depends on the intensity of packets arrival and may even decrease with increasing ρ. This can be explained by the fact that when the channel is highly correlated it is possible to have a long series of slots, where the channel is in "good" condition. The above phenomenon is more pronounced for large values of error burst length B. Fig. 2: Averages for delivery delay as a function of ρ, where m = 10, = 0.1, A = 2.5, at different values for B. Fig.3 shows the total delay as a function of B, where ρ = 0.6, A = 7, m = 10 and m = 0.1. As seen from the graphs the total delay initially decreases and then increases. The reason for this is that from one side at small and medium error burst length, B, the delay of retransmission dominated (see Td and Tq). From other side, by increasing B, the delay of retransmission reduces and hence also reduces the total delay. For large values of B, the delay in the queue has a strong character and the total delay increases (see Tq). 64

65 Computer Systems and Engineering Delay [ms] Tq Td Tt total delay delay in queue delay of delivery Avarage error burst length packet Fig.3: The total delay as a function of B, at ρ = 0.6, A = 7, m = 10 and m= CONCLUSION The performance of mechanism for aggregation with retransmission of fragments is examined through simulations which have been developed by GPSS model. The presence of correlation between the time of feedback and the error burst length through transmission leads to non-trivial results, such as minimizing delays. This can be very important when designing [4] new communication applications for operating in wireless networks using the proposed adaptive mechanism for aggregation. 5. REFERENCES [1] N. Ghazisaidi, M. Maier and C. Assi, Fiber-Wireless (FiWi) Access Networks: A Survey, IEEE Communications Magazine, February 2009, pp [2] J. Xie and X. Wang, A Survey of Mobility Management in Hybrid Wireless Mesh Networks, IEEE Network, November/December 2008, pp [3] J. Hong and K. Sohraby, On Modeling, Analysis, and Optimization of Packet Aggregation Systems, IEEE Transactions on Communications, vol. 58, no. 2, February 2010, pp [4] L. Taneva, Intelligent Module for Data Exchange using CAN Interface, CEMA 09, 8-10 October 2009, Sofia, Proceedings p

66 [5] R. Jain, C. So-In and A. Tamimi, Level Modeling Of IEEE e Mobile Wimax Networks: Key Issues, IEEE Wireless Communications, October 2008, pp [6] V. Hristov,, B. Tudzharov, Adaptive mechanism with aggregation and fragment retransmission for highspeed wireless networks, Bulgarian Journal of Engineering Design, No 7, February 2011, pp (in Bulgarian). [7] Taneva L., R. Bagalev, Testing in electronics manufacturing, FMNS 2011, 8-11 June 2011, Blagoevgrad, Proceedings Volume 1, p

67 Computer Systems and Engineering Experimental Platform for measuring the parameters of magnetization of a transformer in a quasi-static transitional regime Vasil Milovanski, Krasimir Stoyanov, Stefani Milovanska South-West University "Neofit Rilski", Blagoevgrad, Bulgaria HMS Acad. S. P. Corolov", Blagoevgrad, Bulgaria American University in Bulgaria, Blagoevgrad, Bulgaria Abstract: Some opportunities for development of an experimental module for magnetic research have been examined in the current paper. The goal is to attain a more accurate reading of the measured electrical signals which are directly related to the magnetic parameters and characteristics of the ferromagnetic material. Keywords: transformer, magnetic, hysteresis cycles, harmonious components 1. INTRODUCTION Experiments for quasi-static re-magnetization can be conducted by the means of a computer simulation of transitional processes in measuring transformers. [1] The correct approaches for an accurate measurement of the results are looked for in this research paper. This includes some special construction features of the experimental block for measuring and processing the signals, describing the processes of transitional magnetization of the examined object. 2. ANALYSIS OF THE EXPERIMENTAL BLOCK AND OF SOME OF ITS ELEMENTS WHICH ARE USED FOR MEASURING AND PROCESSING OF THE GENERATED RESULTS The tasks related to the study of ferromagnetic materials by the means of computer simulation of transitional magnetization in measuring transformers have been issues of several studies. [1,2] An equivalent scheme of an experimental module is shown on Figure 1. The relationships given in (1) are based on some basic laws of electrical engineering. These relationships relate the electrical and the magnetic parameters of the measuring transformer. 67

68 dφ u 1 = ( R1 + RSH 1) i 1 + w1 dt dφ (1) u 2 = -( R2 + RSH2 ) i 2 + w2 dt i1w1 - i2w 2 = i0w 1 = lav. H Fig. 1: Experimental platform. By the means of these equalities, the relationships between B( t) and H ( t ) can be found, depending on the method of work of the transformer. There are current (CT) and voltage transformers (VT). The respective relationships are shown in (2) and (3). ush1 ush2 u u2 0, i1 ( t) =, i2 ( t) = 1 0, 1( ) = SH RSH 1 R i2 i t, u2 = u2( t) SH2 RSH 1 t t ( R2 + RSH2 ) 1 (2) B( t) = B0 + i2 ( t) dt (3) B( t) = B0 + w2s u2( t) dt 0 w2s 0 1 w1 H ( t) = ( i1w1 - i2w2 ) H ( t) = i1 ( t) lav. lav. Taking into consideration these relationships, it can be concluded that in both cases, the magnetic induction is computed by integrating mathematically either the current ( i2 ( t) dt ) or the voltage ( t 0 t 0 u ( t) dt ) in the secondary coil of the transformer. In practice, this means that the calculation error will be accumulated as a result of the calculation of these signals. The errors may be caused either by inappropriate measuring resistors or by non-ideal operational amplifiers used for amplifying the signals. They may also be caused by improper selection of analog-to-digital converters (ADC), bad topology of the board design, etc. The current paper presents an analysis of the parts of the experimental block that one who wants to get accurate results should pay special attention to Choice of appropriate measuring resistors Rsh1and R sh2 The choice of Rsh1 and R sh 2 is crucial. In order to repeatedly get the same results from the measurement, it is necessary to decrease significantly the influence of the temperature on the value of the resistance. This can be achieved by the means of precise resistors, designed particularly for this purpose. Their parameters are very precise. These resistors are made of alloys, the resistance of which depends on the

69 Computer Systems and Engineering temperature very little. An example of such an alloy is Manganin, which is a trademarked name for an alloy of typically 86% copper, 12% manganese, and 2% nickel. The value of the measuring resistors should be low for two reasons: heat reduction, and insurance of a large dynamic range. However, it is necessary to consider the fact that the tiny value of Rsh may contribute to the measurement of a low voltage with a value close to that of the induced voices. Precise resistors R sh1 and Rsh2 have been used in the conducted research. Their average point and total resistance is Rsh1 ab = R sh2ab = 2* 350,µ Ω, and their own parasitic inductivity is Lsh1 = L sh2 = 2* 2,nH. The constructive and the equivalent schemes are shown in Figure 2. Fig. 2: An equivalent scheme of R. sh Knowing i 1 and i 2, the nominal value of the dispersed power may be found. The maximal current in the particular case discussed is 10, A. Therefore, the dispersed power is the following: 6 Psh 1 = P sh2 = 10* 700* 10 = 70,mW To avoid a phase shift between the inputs of the operational amplifiers, it is necessary to study the influence of the parasitic inductivity on the impedance of the resistor. When the operating frequency is maximal with a value of f = 20,Hz, the impedance is the following: Z sh = 350, µ Ω + j 0. 5, µ Ω. Taking into consideration the generated result, it can be concluded that in the worst case, the measuring resistor has a negligible reactive component, i.e. it has an active character Choice of operational amplifiers The selection of appropriate operational amplifiers starts from the consideration of what signals will be amplified, where the corresponding inputs will be included, and how the coordination between inputs and outputs will be executed. In addition, it is necessary to choose such amplifiers that are not very noisy, have small asymmetries and a high coefficient of reduction of the synphase signals CMRR, etc. Figure 1 represents the different way in which the measuring resistors are connected in the scheme. In contrast to R sh2, R sh1 is connected in series and in a galvanic way with the primary coil of the transformer and the generator of magnetization. Figure 3 represents an experimental platform, and the way the resistors and the operational amplifiers are connected. 69

70 High-quality operational amplifiers produced by Anal og Devices AD8138 are used. [4].They have low levels of private noise, wide frequency band and differential input and output devices. Fig. 3: Experimental block with included operational amplifiers. The inputs of the amplifier A 1 are included in points a and b, which is one half of R sh1. Point G is at the other end of the resistor. It is connected to the common conductor. Thus one of the two halves Rsh1 a is used for measuring the current i 1, while the other half is used for lifting up the source of the signal from the ground. The goal of the latter is to reduce the noise voltage towards the input of the amplifier. [3] The size of the maximal input signal depends on the value of the current I 1 = 10,A, which creates a voltage drop on R sh1a determined by the following equality: U1 ab = R sh1a * I 1 = 3. 5,mV. The scope of this voltage is u = 2 2 * U 9. 9,mV. The choice of a high-quality operational amplifier 1pp 1ab1 with a differential input device allows the typical synphase voltage for the scheme to be reduced, and the asymmetric input to become symmetric at the output. The middle point G of R sh2 has to be connected to the ground on the output side of the transformer. Thus the synphase signals at point G from the two inputs of the amplifier turn out to be in a counter-phase and cancel each other out. The only condition is the following: Rsh2a = R sh2b.the differential signal is the only thing that is amplified in this way Coordination of the operational amplifier output with ADC s input The differential output of AD8138 allows itself to be connected to the differential input of the analog-to-digital converter (ADC) of the type AD7400. This is an ADC with Σ modulator, operating at a relatively high sample rate - 900, khz. The usage of an analog amplifier between Rsh and ADC allows an execution of a bufferization and an easy change of the synphase level. The principle of analog signal sampling is the reason why noise occurs. It is necessary to find a way to reduce this noise. First, this should be done 70

71 Computer Systems and Engineering by reducing the over-sampling. It is characterized by an expansion of the sampling frequency range, which is many times higher than the frequency range of the signal. As a result of the operation of the Σ modulator, the spectrum of the noise sample partly flattens by the process of integration in the scheme itself. However, a large part of the noise belongs to the highfrequency region and can be eliminated by the means of a low-frequency filter of high order. Another component of the noise sample is obtained by the means of superimposing of the spectrum of the signal aliasing. Figure 4 shows that the harmonic components of the input signal, which exceed half of the sampling frequency ( 450 +, khz ), have a mirror image in the operational low-frequency spectrum. When the chosen sampling frequency is high, the harmonic components may be filtrated by the means of a simple RC filter. The usage of filters at the inputs of the two ADC converters leads to a phase shift of the signals, which may change the real general image of the study. Fig. 4: Spectrum of the signals in an ADC. Fig. 5a: A scheme of a RC LPF. A low-frequency filter ( Figure 5a ) with elements R = 1. 0,kΩ andc = 33,nF is used. It has been examined by a computer simulation program in the frequency range from f 1 = 10,Hz to f 2 = 1. 0,MHz. The amplitude frequency ( Figure 5b ) and the phase frequency ( Figure 5c ) characteristics of a LPF are graphically shown. Fig. 5b: RC LPF - АЧХ. Fig. 5c: RC LPF - ФЧХ. 71

Analecta Vol. 8, No. 2 ISSN 2064-7964

Analecta Vol. 8, No. 2 ISSN 2064-7964 EXPERIMENTAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IN ENGINEERING PROCESSING SYSTEM S. Dadvandipour Institute of Information Engineering, University of Miskolc, Egyetemváros, 3515, Miskolc, Hungary,

More information

CHAPTER 6 PRINCIPLES OF NEURAL CIRCUITS.

CHAPTER 6 PRINCIPLES OF NEURAL CIRCUITS. CHAPTER 6 PRINCIPLES OF NEURAL CIRCUITS. 6.1. CONNECTIONS AMONG NEURONS Neurons are interconnected with one another to form circuits, much as electronic components are wired together to form a functional

More information

Neural Networks in Data Mining

Neural Networks in Data Mining IOSR Journal of Engineering (IOSRJEN) ISSN (e): 2250-3021, ISSN (p): 2278-8719 Vol. 04, Issue 03 (March. 2014), V6 PP 01-06 www.iosrjen.org Neural Networks in Data Mining Ripundeep Singh Gill, Ashima Department

More information

Effective Use of Android Sensors Based on Visualization of Sensor Information

Effective Use of Android Sensors Based on Visualization of Sensor Information , pp.299-308 http://dx.doi.org/10.14257/ijmue.2015.10.9.31 Effective Use of Android Sensors Based on Visualization of Sensor Information Young Jae Lee Faculty of Smartmedia, Jeonju University, 303 Cheonjam-ro,

More information

D A T A M I N I N G C L A S S I F I C A T I O N

D A T A M I N I N G C L A S S I F I C A T I O N D A T A M I N I N G C L A S S I F I C A T I O N FABRICIO VOZNIKA LEO NARDO VIA NA INTRODUCTION Nowadays there is huge amount of data being collected and stored in databases everywhere across the globe.

More information

PUF Physical Unclonable Functions

PUF Physical Unclonable Functions Physical Unclonable Functions Protecting next-generation Smart Card ICs with SRAM-based s The use of Smart Card ICs has become more widespread, having expanded from historical banking and telecommunication

More information

REAL TIME MONITORING AND TRACKING SYSTEM FOR AN ITEM USING THE RFID TECHNOLOGY

REAL TIME MONITORING AND TRACKING SYSTEM FOR AN ITEM USING THE RFID TECHNOLOGY Review of the Air Force Academy No 3 (30) 2015 REAL TIME MONITORING AND TRACKING SYSTEM FOR AN ITEM USING THE RFID TECHNOLOGY For the past few years, location systems have become a major studying field,

More information

The Bucharest Academy of Economic Studies, Romania E-mail: ppaul@ase.ro E-mail: catalin.boja@ie.ase.ro

The Bucharest Academy of Economic Studies, Romania E-mail: ppaul@ase.ro E-mail: catalin.boja@ie.ase.ro Paul Pocatilu 1 and Ctlin Boja 2 1) 2) The Bucharest Academy of Economic Studies, Romania E-mail: ppaul@ase.ro E-mail: catalin.boja@ie.ase.ro Abstract The educational process is a complex service which

More information

EFFICIENT DATA PRE-PROCESSING FOR DATA MINING

EFFICIENT DATA PRE-PROCESSING FOR DATA MINING EFFICIENT DATA PRE-PROCESSING FOR DATA MINING USING NEURAL NETWORKS JothiKumar.R 1, Sivabalan.R.V 2 1 Research scholar, Noorul Islam University, Nagercoil, India Assistant Professor, Adhiparasakthi College

More information

The Jigsaw Collaborative Method in Blended Learning Course Computer Games and Education Realization in Moodle

The Jigsaw Collaborative Method in Blended Learning Course Computer Games and Education Realization in Moodle The Jigsaw Collaborative Method in Blended Learning Course Computer Games and Education Realization in Moodle Daniela Tuparova 1, Georgi Tuparov 1,2 1 Department of Computer Science, South-West University,

More information

Application of a Web-based Monitoring and Control system in Plastic Rotational Moulding Machine

Application of a Web-based Monitoring and Control system in Plastic Rotational Moulding Machine Application of a Web-based Monitoring and Control system in Plastic Rotational Moulding Machine Mário Rodrigues 1, José Mendes 2, and Jaime Fonseca 3 University of Minho 1,2,3 Dept. of Industrial Electronics

More information

Introduction to Information Technology

Introduction to Information Technology Introduction to Information Technology Career Cluster Information Technology Course Code 10009 Prerequisite(s) Recommended that a student has taken from the Foundation Courses Computer Applications. Credit.5

More information

Laser Gesture Recognition for Human Machine Interaction

Laser Gesture Recognition for Human Machine Interaction International Journal of Computer Sciences and Engineering Open Access Research Paper Volume-04, Issue-04 E-ISSN: 2347-2693 Laser Gesture Recognition for Human Machine Interaction Umang Keniya 1*, Sarthak

More information

MANAGING QUEUE STABILITY USING ART2 IN ACTIVE QUEUE MANAGEMENT FOR CONGESTION CONTROL

MANAGING QUEUE STABILITY USING ART2 IN ACTIVE QUEUE MANAGEMENT FOR CONGESTION CONTROL MANAGING QUEUE STABILITY USING ART2 IN ACTIVE QUEUE MANAGEMENT FOR CONGESTION CONTROL G. Maria Priscilla 1 and C. P. Sumathi 2 1 S.N.R. Sons College (Autonomous), Coimbatore, India 2 SDNB Vaishnav College

More information

Lecture 1: Introduction to Neural Networks Kevin Swingler / Bruce Graham

Lecture 1: Introduction to Neural Networks Kevin Swingler / Bruce Graham Lecture 1: Introduction to Neural Networks Kevin Swingler / Bruce Graham kms@cs.stir.ac.uk 1 What are Neural Networks? Neural Networks are networks of neurons, for example, as found in real (i.e. biological)

More information

Application of Neural Network in User Authentication for Smart Home System

Application of Neural Network in User Authentication for Smart Home System Application of Neural Network in User Authentication for Smart Home System A. Joseph, D.B.L. Bong, D.A.A. Mat Abstract Security has been an important issue and concern in the smart home systems. Smart

More information

Cloud Computing for Agent-based Traffic Management Systems

Cloud Computing for Agent-based Traffic Management Systems Cloud Computing for Agent-based Traffic Management Systems Manoj A Patil Asst.Prof. IT Dept. Khyamling A Parane Asst.Prof. CSE Dept. D. Rajesh Asst.Prof. IT Dept. ABSTRACT Increased traffic congestion

More information

Research on the Performance Optimization of Hadoop in Big Data Environment

Research on the Performance Optimization of Hadoop in Big Data Environment Vol.8, No.5 (015), pp.93-304 http://dx.doi.org/10.1457/idta.015.8.5.6 Research on the Performance Optimization of Hadoop in Big Data Environment Jia Min-Zheng Department of Information Engineering, Beiing

More information

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY A PATH FOR HORIZING YOUR INNOVATIVE WORK OPEN SOURCE: SIXTH SENSE INTEGRATING INFORMATION WITH THE REAL WORLD MADHURI V.

More information

THE HUMAN BRAIN. observations and foundations

THE HUMAN BRAIN. observations and foundations THE HUMAN BRAIN observations and foundations brains versus computers a typical brain contains something like 100 billion miniscule cells called neurons estimates go from about 50 billion to as many as

More information

What will I learn as an Electrical Engineering student?

What will I learn as an Electrical Engineering student? What will I learn as an Electrical Engineering student? Department of Electrical and Computer Engineering Tu5s School of Engineering Trying to decide on a major? Most college course descrip>ons are full

More information

Visualizing the Teaching / Learning Process through Computer Graphics. Visualizing, technology, computer graphics, education

Visualizing the Teaching / Learning Process through Computer Graphics. Visualizing, technology, computer graphics, education Visualizing the Teaching / Learning Process through Computer Graphics 1 Aghware F. O.; 2 Egbuna E. O.; 3 Aghware A. and 4 Ojugo Arnold 1, 2, 3 Computer Science Department, College of Education, Agbor 4

More information

RADIO FREQUENCY IDENTIFICATION FOR STUDENT ATTENDENCE TRACKING

RADIO FREQUENCY IDENTIFICATION FOR STUDENT ATTENDENCE TRACKING International Journal of Science, Environment and Technology, Vol. 4, No 2, 2015, 468 473 ISSN 2278-3687 (O) 2277-663X (P) RADIO FREQUENCY IDENTIFICATION FOR STUDENT ATTENDENCE TRACKING Anu Sunny, Tharika

More information

Malware Detection in Android by Network Traffic Analysis

Malware Detection in Android by Network Traffic Analysis Malware Detection in Android by Network Traffic Analysis Mehedee Zaman, Tazrian Siddiqui, Mohammad Rakib Amin and Md. Shohrab Hossain Department of Computer Science and Engineering, Bangladesh University

More information

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt. Sensor. Transportation Informatics Group University of Klagenfurt 5/11/2009 1

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt. Sensor. Transportation Informatics Group University of Klagenfurt 5/11/2009 1 Sensor Transportation Informatics Group University of Klagenfurt Alireza Fasih, 2009 5/11/2009 1 Address: L4.2.02, Lakeside Park, Haus B04, Ebene 2, Klagenfurt-Austria Sensor A sensor is a device that

More information

Exercise. Rule #1 Exercise boosts brain power.

Exercise. Rule #1 Exercise boosts brain power. Exercise Rule #1 Exercise boosts brain power. Our brains were built for walking 12 miles a day! To improve your thinking skills, move. Exercise gets blood to your brain, bringing it glucose for energy

More information

The preliminary design of a wearable computer for supporting Construction Progress Monitoring

The preliminary design of a wearable computer for supporting Construction Progress Monitoring The preliminary design of a wearable computer for supporting Construction Progress Monitoring 1 Introduction Jan Reinhardt, TU - Dresden Prof. James H. Garrett,Jr., Carnegie Mellon University Prof. Raimar

More information

ZIMBABWE SCHOOL EXAMINATIONS COUNCIL. COMPUTER STUDIES 7014/01 PAPER 1 Multiple Choice SPECIMEN PAPER

ZIMBABWE SCHOOL EXAMINATIONS COUNCIL. COMPUTER STUDIES 7014/01 PAPER 1 Multiple Choice SPECIMEN PAPER ZIMBABWE SCHOOL EXAMINATIONS COUNCIL General Certificate of Education Ordinary Level COMPUTER STUDIES 7014/01 PAPER 1 Multiple Choice SPECIMEN PAPER Candidates answer on the question paper Additional materials:

More information

International Journal of Electronics and Computer Science Engineering 1449

International Journal of Electronics and Computer Science Engineering 1449 International Journal of Electronics and Computer Science Engineering 1449 Available Online at www.ijecse.org ISSN- 2277-1956 Neural Networks in Data Mining Priyanka Gaur Department of Information and

More information

Performance analysis and comparison of virtualization protocols, RDP and PCoIP

Performance analysis and comparison of virtualization protocols, RDP and PCoIP Performance analysis and comparison of virtualization protocols, RDP and PCoIP Jiri Kouril, Petra Lambertova Department of Telecommunications Brno University of Technology Ustav telekomunikaci, Purkynova

More information

White Paper. Enhancing Website Security with Algorithm Agility

White Paper. Enhancing Website Security with Algorithm Agility ENHANCING WEBSITE SECURITY WITH ALGORITHM AGILITY White Paper Enhancing Website Security with Algorithm Agility Enhancing Website Security with Algorithm Agility Contents Introduction 3 Encryption Today

More information

Fostering Incident Response and Digital Forensics Research

Fostering Incident Response and Digital Forensics Research Fostering Incident Response and Digital Forensics Research Bruce J. Nikkel bruce.nikkel@ubs.com September 8, 2014 Abstract This article highlights different incident response topics with a focus on digital

More information

Intelligent Home Automation and Security System

Intelligent Home Automation and Security System Intelligent Home Automation and Security System Ms. Radhamani N Department of Electronics and communication, VVIET, Mysore, India ABSTRACT: In todays scenario safer home security is required, As the technology

More information

An Application of Data Leakage Prevention System based on Biometrics Signals Recognition Technology

An Application of Data Leakage Prevention System based on Biometrics Signals Recognition Technology Vol.63 (NT 2014), pp.1-5 http://dx.doi.org/10.14257/astl.2014.63.01 An Application of Data Leakage Prevention System based on Biometrics Signals Recognition Technology Hojae Lee 1, Junkwon Jung 1, Taeyoung

More information

Adi Armoni Tel-Aviv University, Israel. Abstract

Adi Armoni Tel-Aviv University, Israel. Abstract Informing Science Data Security Volume 5 No 1, 2002 Data Security Management in Distributed Computer Systems Adi Armoni Tel-Aviv University, Israel armonia@colman.ac.il Abstract This research deals with

More information

INTRUSION PREVENTION AND EXPERT SYSTEMS

INTRUSION PREVENTION AND EXPERT SYSTEMS INTRUSION PREVENTION AND EXPERT SYSTEMS By Avi Chesla avic@v-secure.com Introduction Over the past few years, the market has developed new expectations from the security industry, especially from the intrusion

More information

Snapshots in the Data Warehouse BY W. H. Inmon

Snapshots in the Data Warehouse BY W. H. Inmon Snapshots in the Data Warehouse BY W. H. Inmon There are three types of modes that a data warehouse is loaded in: loads from archival data loads of data from existing systems loads of data into the warehouse

More information

Students' Interests and Decision-Making in the Learning of "Social Impact of Technology"

Students' Interests and Decision-Making in the Learning of Social Impact of Technology Students' Interests and Decision-Making in the Learning of "Social Impact of Technology" Jun Moriyama Ph.D, Hyogo University of Teacher Education, Hyogo, Japan junmori@life.hyogo-u.ac.jp Kentaro Shiratani

More information

Neural Network and Genetic Algorithm Based Trading Systems. Donn S. Fishbein, MD, PhD Neuroquant.com

Neural Network and Genetic Algorithm Based Trading Systems. Donn S. Fishbein, MD, PhD Neuroquant.com Neural Network and Genetic Algorithm Based Trading Systems Donn S. Fishbein, MD, PhD Neuroquant.com Consider the challenge of constructing a financial market trading system using commonly available technical

More information

Autonomous Advertising Mobile Robot for Exhibitions, Developed at BMF

Autonomous Advertising Mobile Robot for Exhibitions, Developed at BMF Autonomous Advertising Mobile Robot for Exhibitions, Developed at BMF Kucsera Péter (kucsera.peter@kvk.bmf.hu) Abstract In this article an autonomous advertising mobile robot that has been realized in

More information

OCR LEVEL 3 CAMBRIDGE TECHNICAL

OCR LEVEL 3 CAMBRIDGE TECHNICAL Cambridge TECHNICALS OCR LEVEL 3 CAMBRIDGE TECHNICAL CERTIFICATE/DIPLOMA IN IT EXPLORING COMPUTER APPLICATIONS M/505/5403 LEVEL 3 UNIT 36 GUIDED LEARNING HOURS: 60 UNIT CREDIT VALUE: 10 EXPLORING COMPUTER

More information

Prediction of DDoS Attack Scheme

Prediction of DDoS Attack Scheme Chapter 5 Prediction of DDoS Attack Scheme Distributed denial of service attack can be launched by malicious nodes participating in the attack, exploit the lack of entry point in a wireless network, and

More information

Open Access Research on Application of Neural Network in Computer Network Security Evaluation. Shujuan Jin *

Open Access Research on Application of Neural Network in Computer Network Security Evaluation. Shujuan Jin * Send Orders for Reprints to reprints@benthamscience.ae 766 The Open Electrical & Electronic Engineering Journal, 2014, 8, 766-771 Open Access Research on Application of Neural Network in Computer Network

More information

Comparison of K-means and Backpropagation Data Mining Algorithms

Comparison of K-means and Backpropagation Data Mining Algorithms Comparison of K-means and Backpropagation Data Mining Algorithms Nitu Mathuriya, Dr. Ashish Bansal Abstract Data mining has got more and more mature as a field of basic research in computer science and

More information

Automated Profile Vehicle Using GSM Modem, GPS and Media Processor DM642

Automated Profile Vehicle Using GSM Modem, GPS and Media Processor DM642 2009 International Conference on Computer Engineering and Applications IPCSIT vol.2 (2011) (2011) IACSIT Press, Singapore Automated Profile Vehicle Using GSM Modem, GPS and Media Processor DM642 Muhammad

More information

Fuzzy Cognitive Map for Software Testing Using Artificial Intelligence Techniques

Fuzzy Cognitive Map for Software Testing Using Artificial Intelligence Techniques Fuzzy ognitive Map for Software Testing Using Artificial Intelligence Techniques Deane Larkman 1, Masoud Mohammadian 1, Bala Balachandran 1, Ric Jentzsch 2 1 Faculty of Information Science and Engineering,

More information

Submitted by: Jinyoung Kim (997864173) Rowa Karkokli (992424159)

<ECE1778H> Submitted by: Jinyoung Kim (997864173) Rowa Karkokli (992424159) Submitted by: Jinyoung Kim (997864173) Rowa Karkokli (992424159) Date: April 12, 2011 EXECITIVE SUMMARY: Dementia is a cognitive disorder resulting in loss of memory, changes in personality,

More information

Course Bachelor of Information Technology majoring in Network Security or Data Infrastructure Engineering

Course Bachelor of Information Technology majoring in Network Security or Data Infrastructure Engineering Course Bachelor of Information Technology majoring in Network Security or Data Infrastructure Engineering Course Number HE20524 Location Meadowbank OVERVIEW OF SUBJECT REQUIREMENTS Note: This document

More information

Summer projects for Dept. of IT students in the summer 2015

Summer projects for Dept. of IT students in the summer 2015 Summer projects for Dept. of IT students in the summer 2015 Here are 7 possible summer project topics for students. If you are interested in any of them, contact the person associated with the project

More information

Designing and Embodiment of Software that Creates Middle Ware for Resource Management in Embedded System

Designing and Embodiment of Software that Creates Middle Ware for Resource Management in Embedded System , pp.97-108 http://dx.doi.org/10.14257/ijseia.2014.8.6.08 Designing and Embodiment of Software that Creates Middle Ware for Resource Management in Embedded System Suk Hwan Moon and Cheol sick Lee Department

More information

CARDA: Content Management Systems for Augmented Reality with Dynamic Annotation

CARDA: Content Management Systems for Augmented Reality with Dynamic Annotation , pp.62-67 http://dx.doi.org/10.14257/astl.2015.90.14 CARDA: Content Management Systems for Augmented Reality with Dynamic Annotation Byeong Jeong Kim 1 and Seop Hyeong Park 1 1 Department of Electronic

More information

Data Transfer Technology to Enable Communication between Displays and Smart Devices

Data Transfer Technology to Enable Communication between Displays and Smart Devices Data Transfer Technology to Enable Communication between Displays and Smart Devices Kensuke Kuraki Shohei Nakagata Ryuta Tanaka Taizo Anan Recently, the chance to see videos in various places has increased

More information

Image Estimation Algorithm for Out of Focus and Blur Images to Retrieve the Barcode Value

Image Estimation Algorithm for Out of Focus and Blur Images to Retrieve the Barcode Value IJSTE - International Journal of Science Technology & Engineering Volume 1 Issue 10 April 2015 ISSN (online): 2349-784X Image Estimation Algorithm for Out of Focus and Blur Images to Retrieve the Barcode

More information

A Storage Architecture for High Speed Signal Processing: Embedding RAID 0 on FPGA

A Storage Architecture for High Speed Signal Processing: Embedding RAID 0 on FPGA Journal of Signal and Information Processing, 12, 3, 382-386 http://dx.doi.org/1.4236/jsip.12.335 Published Online August 12 (http://www.scirp.org/journal/jsip) A Storage Architecture for High Speed Signal

More information

Applying Deep Learning to Car Data Logging (CDL) and Driver Assessor (DA) October 22-Oct-15

Applying Deep Learning to Car Data Logging (CDL) and Driver Assessor (DA) October 22-Oct-15 Applying Deep Learning to Car Data Logging (CDL) and Driver Assessor (DA) October 22-Oct-15 GENIVI is a registered trademark of the GENIVI Alliance in the USA and other countries Copyright GENIVI Alliance

More information

Brain Basics: A Brain in Sync

Brain Basics: A Brain in Sync Brain Basics: A Brain in Sync By: Dr. Robert Melillo The idea of a functional relationship between the left and right sides of the brain is hardly new. In 1949, Canadian neuropsychologist Donald O. Hebb,

More information

Alaa Alhamami, Avan Sabah Hamdi Amman Arab University Amman, Jordan

Alaa Alhamami, Avan Sabah Hamdi Amman Arab University Amman, Jordan World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 5, No. 5, 87-91, 2015 Mobile Secure Transmission Method Based on Audio Steganography Alaa Alhamami, Avan Sabah

More information

B. Questions and answers 74. Youthpass in practice. Youthpass in Training Courses. 1 What is Youthpass in Training Courses?

B. Questions and answers 74. Youthpass in practice. Youthpass in Training Courses. 1 What is Youthpass in Training Courses? B. Questions and answers 74 B4 Youthpass in practice Mark Taylor 1 What is? The simple answer is that is a Certificate which describes the activity itself and confirms the participation of a youth worker/youth

More information

ANDROID APPLICATION DEVELOPMENT FOR ENVIRONMENT MONITORING USING SMART PHONES

ANDROID APPLICATION DEVELOPMENT FOR ENVIRONMENT MONITORING USING SMART PHONES ANDROID APPLICATION DEVELOPMENT FOR ENVIRONMENT MONITORING USING SMART PHONES ABSTRACT K. Krishnakanth 1 and P. Kavipriya 2 1 M.E Embedded Systems, Sathyabama University, Chennai, India. krishnakoneru99@gmail.com

More information

A SIMULATOR FOR LOAD BALANCING ANALYSIS IN DISTRIBUTED SYSTEMS

A SIMULATOR FOR LOAD BALANCING ANALYSIS IN DISTRIBUTED SYSTEMS Mihai Horia Zaharia, Florin Leon, Dan Galea (3) A Simulator for Load Balancing Analysis in Distributed Systems in A. Valachi, D. Galea, A. M. Florea, M. Craus (eds.) - Tehnologii informationale, Editura

More information

Computational Intelligence Introduction

Computational Intelligence Introduction Computational Intelligence Introduction Farzaneh Abdollahi Department of Electrical Engineering Amirkabir University of Technology Fall 2011 Farzaneh Abdollahi Neural Networks 1/21 Fuzzy Systems What are

More information

Robot Perception Continued

Robot Perception Continued Robot Perception Continued 1 Visual Perception Visual Odometry Reconstruction Recognition CS 685 11 Range Sensing strategies Active range sensors Ultrasound Laser range sensor Slides adopted from Siegwart

More information

Mobile Technologies Index

Mobile Technologies Index www.pwc.com/technology Technology Institute Mobile Technologies Index Mobile operating system: Smartphones will just get smarter By Raman Chitkara, Global Technology Industry Leader The smartphone seems

More information

Lecture 2, Human cognition

Lecture 2, Human cognition Human Cognition An important foundation for the design of interfaces is a basic theory of human cognition The information processing paradigm (in its most simple form). Human Information Processing The

More information

Fuzzy Knowledge Base System for Fault Tracing of Marine Diesel Engine

Fuzzy Knowledge Base System for Fault Tracing of Marine Diesel Engine Fuzzy Knowledge Base System for Fault Tracing of Marine Diesel Engine 99 Fuzzy Knowledge Base System for Fault Tracing of Marine Diesel Engine Faculty of Computers and Information Menufiya University-Shabin

More information

Passion for Innovation

Passion for Innovation Passion for Innovation A Complete Solution Hardware All the Alveo servers are designed and optimized to manage the home automation system. They arebuilt for continuous operation with fanless processing

More information

A Robust Method for Solving Transcendental Equations

A Robust Method for Solving Transcendental Equations www.ijcsi.org 413 A Robust Method for Solving Transcendental Equations Md. Golam Moazzam, Amita Chakraborty and Md. Al-Amin Bhuiyan Department of Computer Science and Engineering, Jahangirnagar University,

More information

A.Giusti, C.Zocchi, A.Adami, F.Scaramellini, A.Rovetta Politecnico di Milano Robotics Laboratory

A.Giusti, C.Zocchi, A.Adami, F.Scaramellini, A.Rovetta Politecnico di Milano Robotics Laboratory Methodology of evaluating the driver's attention and vigilance level in an automobile transportation using intelligent sensor architecture and fuzzy logic A.Giusti, C.Zocchi, A.Adami, F.Scaramellini, A.Rovetta

More information

Mobile Device and Technology Characteristics Impact on Mobile Application Testing

Mobile Device and Technology Characteristics Impact on Mobile Application Testing 13 Mobile Device and Technology Characteristics Impact on Mobile Application Testing TINA SCHWEIGHOFER AND MARJAN HERIČKO, University of Maribor Mobile technologies have a significant impact on processes

More information

Improving Decision Making and Managing Knowledge

Improving Decision Making and Managing Knowledge Improving Decision Making and Managing Knowledge Decision Making and Information Systems Information Requirements of Key Decision-Making Groups in a Firm Senior managers, middle managers, operational managers,

More information

SIP Registration Stress Test

SIP Registration Stress Test SIP Registration Stress Test Miroslav Voznak and Jan Rozhon Department of Telecommunications VSB Technical University of Ostrava 17. listopadu 15/2172, 708 33 Ostrava Poruba CZECH REPUBLIC miroslav.voznak@vsb.cz,

More information

ISSN: 2319-5967 ISO 9001:2008 Certified International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 2, Issue 3, May 2013

ISSN: 2319-5967 ISO 9001:2008 Certified International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 2, Issue 3, May 2013 Transistor Level Fault Finding in VLSI Circuits using Genetic Algorithm Lalit A. Patel, Sarman K. Hadia CSPIT, CHARUSAT, Changa., CSPIT, CHARUSAT, Changa Abstract This paper presents, genetic based algorithm

More information

Implementation of Knock Based Security System

Implementation of Knock Based Security System Implementation of Knock Based Security System Gunjan Jewani Student, Department of Computer science & Engineering, Nagpur Institute of Technology, Nagpur, India ABSTRACT: Security is one of the most critical

More information

IAI : Biological Intelligence and Neural Networks

IAI : Biological Intelligence and Neural Networks IAI : Biological Intelligence and Neural Networks John A. Bullinaria, 2005 1. How do Humans do Intelligent Things? 2. What are Neural Networks? 3. What are Artificial Neural Networks used for? 4. Introduction

More information

interactive product brochure :: Nina: The Virtual Assistant for Mobile Customer Service Apps

interactive product brochure :: Nina: The Virtual Assistant for Mobile Customer Service Apps interactive product brochure :: Nina: The Virtual Assistant for Mobile Customer Service Apps This PDF contains embedded interactive features. Make sure to download and save the file to your computer to

More information

Introduction. Chapter 1. 1.1 Scope of Electrical Engineering

Introduction. Chapter 1. 1.1 Scope of Electrical Engineering Chapter 1 Introduction 1.1 Scope of Electrical Engineering In today s world, it s hard to go through a day without encountering some aspect of technology developed by electrical engineers. The impact has

More information

A SURVEY ON GENETIC ALGORITHM FOR INTRUSION DETECTION SYSTEM

A SURVEY ON GENETIC ALGORITHM FOR INTRUSION DETECTION SYSTEM A SURVEY ON GENETIC ALGORITHM FOR INTRUSION DETECTION SYSTEM MS. DIMPI K PATEL Department of Computer Science and Engineering, Hasmukh Goswami college of Engineering, Ahmedabad, Gujarat ABSTRACT The Internet

More information

Software Development for Multiple OEMs Using Tool Configured Middleware for CAN Communication

Software Development for Multiple OEMs Using Tool Configured Middleware for CAN Communication 01PC-422 Software Development for Multiple OEMs Using Tool Configured Middleware for CAN Communication Pascal Jost IAS, University of Stuttgart, Germany Stephan Hoffmann Vector CANtech Inc., USA Copyright

More information

A Noble Integrated Management System based on Mobile and Cloud service for preventing various hazards

A Noble Integrated Management System based on Mobile and Cloud service for preventing various hazards , pp.166-171 http://dx.doi.org/10.14257/astl.205.98.42 A Noble Integrated Management System based on Mobile and Cloud service for preventing various hazards Yeo ChangSub 1, Ryu HyunKi 1 and Lee HaengSuk

More information

Introduction to Computer Networks and Data Communications

Introduction to Computer Networks and Data Communications Introduction to Computer Networks and Data Communications Chapter 1 Learning Objectives After reading this chapter, you should be able to: Define the basic terminology of computer networks Recognize the

More information

Name of pattern types 1 Process control patterns 2 Logic architectural patterns 3 Organizational patterns 4 Analytic patterns 5 Design patterns 6

Name of pattern types 1 Process control patterns 2 Logic architectural patterns 3 Organizational patterns 4 Analytic patterns 5 Design patterns 6 The Researches on Unified Pattern of Information System Deng Zhonghua,Guo Liang,Xia Yanping School of Information Management, Wuhan University Wuhan, Hubei, China 430072 Abstract: This paper discusses

More information

Healthcare Measurement Analysis Using Data mining Techniques

Healthcare Measurement Analysis Using Data mining Techniques www.ijecs.in International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 03 Issue 07 July, 2014 Page No. 7058-7064 Healthcare Measurement Analysis Using Data mining Techniques 1 Dr.A.Shaik

More information

What will I learn as an Electrical Engineering student?

What will I learn as an Electrical Engineering student? What will I learn as an Electrical Engineering student? Department of Electrical and Computer Engineering Tufts School of Engineering Trying to decide on a major? Most college course descriptions are full

More information

Artificial Intelligence for ICT Innovation

Artificial Intelligence for ICT Innovation 2016 ICT 산업전망컨퍼런스 Artificial Intelligence for ICT Innovation October 5, 2015 Sung-Bae Cho Dept. of Computer Science, Yonsei University http://sclab.yonsei.ac.kr Subjective AI Hype Cycle Expert System Neural

More information

Computer. Welcome to the Faculty of Electrical Engineering, Mathematics and Computer Science! master s degree

Computer. Welcome to the Faculty of Electrical Engineering, Mathematics and Computer Science! master s degree master s degree Computer Science Welcome to the Faculty of Electrical Engineering, Mathematics and Computer Science! For us the world is flat. Electrical Engineering, Mathematics and Computer Science have

More information

Social Innovation through Utilization of Big Data

Social Innovation through Utilization of Big Data Social Innovation through Utilization of Big Data Hitachi Review Vol. 62 (2013), No. 7 384 Shuntaro Hitomi Keiro Muro OVERVIEW: The analysis and utilization of large amounts of actual operational data

More information

Dong-Joo Kang* Dong-Kyun Kang** Balho H. Kim***

Dong-Joo Kang* Dong-Kyun Kang** Balho H. Kim*** Visualization Issues of Mass Data for Efficient HMI Design on Control System in Electric Power Industry Visualization in Computerized Operation & Simulation Tools Dong-Joo Kang* Dong-Kyun Kang** Balho

More information

Memory Allocation Technique for Segregated Free List Based on Genetic Algorithm

Memory Allocation Technique for Segregated Free List Based on Genetic Algorithm Journal of Al-Nahrain University Vol.15 (2), June, 2012, pp.161-168 Science Memory Allocation Technique for Segregated Free List Based on Genetic Algorithm Manal F. Younis Computer Department, College

More information

BOOSTING - A METHOD FOR IMPROVING THE ACCURACY OF PREDICTIVE MODEL

BOOSTING - A METHOD FOR IMPROVING THE ACCURACY OF PREDICTIVE MODEL The Fifth International Conference on e-learning (elearning-2014), 22-23 September 2014, Belgrade, Serbia BOOSTING - A METHOD FOR IMPROVING THE ACCURACY OF PREDICTIVE MODEL SNJEŽANA MILINKOVIĆ University

More information

The Basics of System Dynamics: Discrete vs. Continuous Modelling of Time 1

The Basics of System Dynamics: Discrete vs. Continuous Modelling of Time 1 The Basics of System Dynamics: Discrete vs. Continuous Modelling of Time 1 Günther Ossimitz 2 Maximilian Mrotzek 3 University of Klagenfurt Department of Mathematics Universitätsstrasse 65 9020 Klagenfurt,

More information

Security Threats on National Defense ICT based on IoT

Security Threats on National Defense ICT based on IoT , pp.94-98 http://dx.doi.org/10.14257/astl.205.97.16 Security Threats on National Defense ICT based on IoT Jin-Seok Yang 1, Ho-Jae Lee 1, Min-Woo Park 1 and Jung-ho Eom 2 1 Department of Computer Engineering,

More information

Broadband Networks. Prof. Dr. Abhay Karandikar. Electrical Engineering Department. Indian Institute of Technology, Bombay. Lecture - 29.

Broadband Networks. Prof. Dr. Abhay Karandikar. Electrical Engineering Department. Indian Institute of Technology, Bombay. Lecture - 29. Broadband Networks Prof. Dr. Abhay Karandikar Electrical Engineering Department Indian Institute of Technology, Bombay Lecture - 29 Voice over IP So, today we will discuss about voice over IP and internet

More information

OCR LEVEL 3 CAMBRIDGE TECHNICAL

OCR LEVEL 3 CAMBRIDGE TECHNICAL Cambridge TECHNICALS OCR LEVEL 3 CAMBRIDGE TECHNICAL CERTIFICATE/DIPLOMA IN IT NETWORKED SYSTEMS SECURITY J/601/7332 LEVEL 3 UNIT 28 GUIDED LEARNING HOURS: 60 UNIT CREDIT VALUE: 10 NETWORKED SYSTEMS SECURITY

More information

KNOWLEDGE-BASED IN MEDICAL DECISION SUPPORT SYSTEM BASED ON SUBJECTIVE INTELLIGENCE

KNOWLEDGE-BASED IN MEDICAL DECISION SUPPORT SYSTEM BASED ON SUBJECTIVE INTELLIGENCE JOURNAL OF MEDICAL INFORMATICS & TECHNOLOGIES Vol. 22/2013, ISSN 1642-6037 medical diagnosis, ontology, subjective intelligence, reasoning, fuzzy rules Hamido FUJITA 1 KNOWLEDGE-BASED IN MEDICAL DECISION

More information

Study on the Patterns of Library Resource Construction and Services in MOOC

Study on the Patterns of Library Resource Construction and Services in MOOC , pp. 85-90 http://dx.doi.org/10.14257/ijunesst.2014.7.6.08 Study on the Patterns of Library Resource Construction and Services in MOOC Sun Ji-zhou, Liao Sheng-feng (Library of Nanchang Hangkong University,

More information

Which Design Is Best?

Which Design Is Best? Which Design Is Best? Which Design Is Best? In Investigation 2-8: Which Design Is Best? students will become more familiar with the four basic epidemiologic study designs, learn to identify several strengths

More information

The Cyber Threat Profiler

The Cyber Threat Profiler Whitepaper The Cyber Threat Profiler Good Intelligence is essential to efficient system protection INTRODUCTION As the world becomes more dependent on cyber connectivity, the volume of cyber attacks are

More information